By converting spoken language into written text, these APIs open new possibilities for accessibility, productivity, and user interaction across numerous platforms and devices. As we delve into the intricacies of speech-to-text technology, it’s essential to understand both the foundational components and the advanced mechanisms that drive these systems.

The purpose of this article is to delve into the best speech-to-text API solutions available in 2024, focusing on their technical aspects, industry applications, and advantages.

What is Behind Speech-to-Text API Technology?

Speech-to-text APIs have become an integral part of modern technology, enabling a wide range of applications from automated transcriptions to voice-controlled interfaces. Understanding the underlying technology helps in appreciating the complexity and the advancements that make these APIs so powerful. Here’s a deep dive into the technical aspects of speech-to-text API technology:

Core Components of Speech-to-Text Technology

1. Automatic Speech Recognition (ASR):

• • Acoustic Modeling: Represents the relationship between phonetic units of speech and the corresponding audio signals. This involves:
    • Phoneme Recognition: Identifying the smallest units of sound in speech.
    • Feature Extraction: Converting raw audio signals into a format that the ASR system can process, typically involving the extraction of features like Mel-frequency cepstral coefficients (MFCCs).
  • Language Modeling: Utilizes statistical models to predict word sequences, thereby enhancing the accuracy of transcription. Techniques include:
    • N-gram Models: Probabilistic models that predict the next word in a sequence based on the previous ‘n’ words.
• Neural Language Models: Use deep learning to predict word sequences with greater context and accuracy.

2. Deep Learning and Neural Networks:

• • Recurrent Neural Networks (RNNs): Specialized for sequence data, RNNs are adept at processing sequences of audio signals. Variants like Long Short-Term Memory (LSTM) networks are particularly effective in handling long-range dependencies in speech.
  • Convolutional Neural Networks (CNNs): Primarily used for image processing, CNNs have found applications in speech recognition by helping to identify features in audio spectrograms.
  • Transformer Models: The latest advancement in deep learning, transformer models use attention mechanisms to focus on important parts of the input sequence, significantly improving the accuracy and efficiency of speech-to-text systems.

3. Real-Time Processing:

• • Streaming APIs: Enable continuous transcription of audio in real-time, which is essential for applications like live captioning and interactive voice response systems.
  • On-Device Processing: Reduces latency and dependency on cloud services by performing speech recognition directly on the user’s device. This approach is particularly beneficial for applications requiring immediate response and enhanced privacy.

4. Post-Processing and Error Correction:

• • Text Normalization: Converts transcribed text into a more readable format by addressing issues like punctuation, capitalization, and spacing.
  • Contextual Understanding: Advanced speech-to-text systems incorporate contextual understanding to correct errors based on the surrounding text, improving the overall accuracy of the transcription.

Speech-to-Text APIs Industry Applications

Speech-to-text technology is utilized across various industries, each benefiting from its unique capabilities. Here is a table summarizing the applications in different industries:

Advancements in Speech-to-Text Technology

Recent advancements have significantly improved the capabilities of speech-to-text APIs:

• Multilingual Support: Modern APIs support a wide range of languages and dialects, making them accessible to a global audience.
• Enhanced Accuracy: Continuous improvements in deep learning models and large-scale datasets have led to higher transcription accuracy.
• Privacy and Security: On-device processing and encrypted data transmission ensure that user data remains secure, addressing privacy concerns.

Challenges and Future Directions

While speech-to-text technology has come a long way, it still faces several challenges:

• Accurate Transcription in Noisy Environments: Background noise can significantly impact the accuracy of transcriptions. Advanced noise-cancellation algorithms and robust acoustic models are being developed to address this issue.
• Dialect and Accent Variability: Ensuring accurate transcription across different dialects and accents remains a challenge. Ongoing research focuses on creating more inclusive models that can handle diverse speech patterns.
• Real-Time Translation: Integrating speech-to-text with real-time translation presents both a challenge and an opportunity. Achieving seamless translation while maintaining accuracy is a key area of development.

Best Speech-to-Text API Solutions in 2024

Here are some of the top speech-to-text API solutions available in 2024, based on extensive research from reputable sources such as Deepgram, AssemblyAI, and others​​:

1. Assembly AI

Assembly AI is a leading provider of speech-to-text solutions, known for its high accuracy and advanced machine learning models. It supports multiple languages and dialects, making it a versatile choice for various industries.

Assembly AI

4.7 out of 5 stars

Key features

• High accuracy with advanced machine learning models.
• Support for multiple languages and dialects.
• Real-time and batch processing capabilities.

Pros

• Excellent accuracy for various accents and dialects.
• Flexible integration options with APIs and SDKs.
• Robust support and documentation.

Cons

• Requires significant computational resources for processing.
• Limited offline capabilities.

Use Cases: Suitable for transcription services, call centers, and media industries.

2. Deepgram

Deepgram offers deep learning-based ASR with customizable models, providing high accuracy and fast processing speeds. It integrates seamlessly with various platforms, making it ideal for voice assistants and call analytics.

Deepgram

4.5 out of 5 stars

Key features

• Deep learning-based ASR with customizable models.
• High accuracy and fast processing speeds.
• Integration with various platforms via APIs.

Pros

• Highly scalable for large-scale applications.
• Offers real-time and batch processing options.
• Supports multiple languages and dialects.

Cons

• Customization may require technical expertise.
• Premium features can be costly.

Use Cases: Ideal for voice assistants, transcription, and call analytics.

3. Speechmatics

Speechmatics is renowned for its universal speech recognition technology, offering high accuracy across diverse accents and dialects. It is particularly useful for enterprise applications, providing scalable solutions for various industries.

Speechmatics

4.6 out of 5 stars

Key features

• Universal speech recognition with high accuracy.
• Support for diverse accents and dialects.
• Scalable solutions for enterprise applications.

Pros

• Highly accurate transcription across various dialects.
• Strong enterprise support and scalability.
• Continuous improvements and updates.

Cons

• Setup can be complex for new users.
• Higher cost for extensive usage.

Use Cases: Useful for broadcast media, telecommunication, and transcription services.

4. Rev AI

Rev AI stands out with its industry-leading accuracy, offering human-reviewed options for even higher precision. It supports real-time and asynchronous transcription, making it perfect for media production and legal sectors.

Rev AI

4.4 out of 5 stars

Key features

• Industry-leading accuracy with human-reviewed options.
• Real-time and asynchronous transcription.
• Easy integration with SDKs and APIs.

Pros

• Highly accurate transcriptions with human review.
• Versatile integration options for various platforms.
• Strong reputation in the industry.

Cons

• Human-reviewed transcriptions can be more expensive.
• Limited free tier options.

Use Cases: Perfect for media production, legal, and education sectors.

5. Whisper

Whisper, developed by OpenAI, is a cutting-edge speech recognition technology offering high accuracy and robust performance. It supports multiple languages and is ideal for developers seeking open-source solutions.

Whisper

4.3 out of 5 stars

Key features

• OpenAI’s cutting-edge speech recognition technology.
• High accuracy and robust performance.
• Support for multiple languages.

Pros

• Open-source and customizable.
• Strong performance across various languages.
• Free to use with extensive documentation.

Cons

• May require fine-tuning for specific applications.
• Limited support compared to commercial solutions.

Use Cases: Suitable for developers seeking open-source solutions for diverse applications.

6. Symbl

Symbl offers advanced conversational intelligence with contextual understanding, providing real-time transcription and analysis. It integrates well with communication platforms, making it ideal for customer service and team collaboration.

Symbl

4.2 out of 5 stars

Key features

• Conversational intelligence with contextual understanding.
• Real-time transcription and analysis.
• Integration with communication platforms.

Pros

• Advanced contextual understanding enhances transcription accuracy.
• Seamless integration with various communication tools.
• Offers real-time insights and analytics.

Cons

• Can be complex to integrate without technical expertise.
• Some features are available only in premium plans.

Use Cases: Ideal for customer service, sales, and team collaboration tools.

Krisp: The Ultimate Transcription Solution for Call Centers

Krisp is a versatile and reliable transcription software designed to enhance call center operations and improve customer service.

Technical Advantages of Krisp for Enterprise Call Centers

• Superior Transcription Accuracy

  • 96% Accuracy: Leveraging cutting-edge AI, Krisp ensures high-quality transcriptions even in noisy environments, boasting a Word Error Rate (WER) of only 4%.

  On-Device Processing

  • Enhanced Security: Krisp’s desktop app processes transcriptions and noise cancellation directly on your device, ensuring sensitive information remains secure and compliant with stringent security standards.

  Unmatched Privacy

  • Real-Time Redaction: Ensures the utmost privacy by redacting Personally Identifiable Information (PII) and Payment Card Information (PCI) in real-time.
  • Private Cloud Storage: Stores transcripts in a private cloud owned by customers, with write-only access, ensuring complete control over data.

  Centralized Solution Across All Platforms

  • Cost Optimization: By centralizing call transcriptions across all platforms, Krisp CCT optimizes costs and simplifies data management.
  • Streamlined Operations: Eliminates the need for multiple transcription services, making data handling more efficient.

  No Additional Integrations Required

  • Effortless Integration: Krisp’s plug-and-play setup integrates seamlessly with major Contact Center as a Service (CCaaS) and Unified Communications as a Service (UCaaS) platforms.
  • Operational Efficiency: Requires no additional configurations, ensuring smooth and secure operations from the start.

Use Cases Enabled by Krisp Call Center Transcription

Use Case	Description
Enhancing Call Center Efficiency	Boost your BPO’s efficiency by ensuring quality control of customer interactions, enabling targeted training and coaching sessions, refining sales strategies, and improving call center metrics for an enhanced operation.
Better Compliance and Record-Keeping	Maintain regulatory compliance and adhere to industry standards with Krisp CCT, which provides a searchable record of all customer interactions. This can support your compliance efforts and offer valuable information for dispute resolution.
Enabling Customer Intel Gathering	Streamline customer research and analysis, identify actionable customer insights, and collect feature requests to better understand and serve your customers.
Fortifying Fraud Detection	Identify fraudulent patterns in customer interactions, mitigate data breaches, and enhance fraud prevention strategies to protect your business and customers with Krisp CCT.

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Speech-To-Text API Frequently Asked Questions

Which Speech-to-Text API is the best?

The best Speech-to-Text API depends on specific needs such as accuracy, real-time capabilities, language support, and integration requirements. Top contenders include Assembly AI, Deepgram, and Speechmatics.

Which text-to-speech API is realistic?

APIs like Google Text-to-Speech and Amazon Polly offer highly realistic text-to-speech capabilities, providing natural-sounding voices and extensive language support.

Is there any free Speech-to-Text API?

Yes, several providers offer free tiers or open-source options. For instance, OpenAI’s Whisper is available for free and supports multiple languages, making it accessible for small-scale applications and testing.

Is Google Text-to-Speech API free?

Google Text-to-Speech API offers a free tier with limited usage, making it accessible for small-scale applications and testing. For larger-scale use, paid plans are available with more features and higher usage limits.

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How Speech-to-Text Technology Works

Understanding the mechanics behind speech-to-text technology is crucial for appreciating its benefits. Here’s a detailed breakdown of the process:

Step-by-Step Process

1. Audio Input: The process begins with capturing audio via a microphone or telephony system.
   • Microphone Specifications: High-quality microphones ensure clarity. Specifications like sensitivity, frequency response, and signal-to-noise ratio (SNR) are critical.
   • Telephony Systems: Digital systems are preferred for their noise reduction capabilities and higher fidelity compared to analog systems.
2. Pre-Processing: The captured audio is cleaned up to remove background noise and enhance clarity.
   • Noise Reduction Algorithms: Techniques like spectral subtraction, Wiener filtering, and deep learning-based denoising are employed.
   • Echo Cancellation: Important in telephony, it removes echoes that can confuse the transcription algorithms.
3. Feature Extraction: Key features from the audio, such as phonemes, are extracted and analyzed.
   • Acoustic Feature Extraction: Methods like Mel-frequency cepstral coefficients (MFCCs) and spectrogram analysis are used to capture important audio features.
   • Temporal Features: Techniques like dynamic time warping (DTW) help in aligning sequences of varying speeds.
4. Acoustic Model: These features are then matched against an acoustic model that represents the sounds of a language.
   • Hidden Markov Models (HMMs): Traditional models that segment and recognize patterns in the audio data.
   • Deep Neural Networks (DNNs): More advanced models that provide higher accuracy by learning complex patterns in large datasets.
5. Language Model: The matched sounds are processed using a language model to form coherent words and sentences.
   • N-grams and Statistical Models: Used to predict the next word in a sequence based on the probability of word combinations.
   • Recurrent Neural Networks (RNNs) and Transformers: Modern approaches that handle longer dependencies and context, leading to more accurate transcriptions.
6. Text Output: Finally, the processed data is converted into text and displayed in real-time.
   • Real-time Text Rendering: Ensures minimal delay between speech and text output, crucial for live applications.
   • Post-Processing: Includes tasks like punctuation addition, capitalization, and correcting common transcription errors.

Leading Use Cases of Streaming Speech-to-Text Technology

Streaming Speech-to-Text technology has a wide range of use cases across various industries and applications. This technology, which converts spoken language into written text in real-time, is proving to be invaluable for enhancing communication, accessibility, and productivity. Here are some key industries and how they are utilizing Streaming Speech-to-Text technology:

Call Centers

• Enhanced Customer Service: Immediate transcription helps in better understanding customer issues and providing quick resolutions.
  • Real-Time Assistance: Transcripts enable supervisors to provide real-time guidance to agents during calls.
  • Customer History: Agents can quickly review previous transcripts to understand the customer’s history.
• Operational Efficiency: Reduces the time spent on manual note-taking and data entry.
  • Automated Workflows: Integration with CRM systems can automate task creation based on call transcripts.
  • Resource Allocation: Transcripts help in analyzing call volumes and adjusting staffing levels accordingly.
• Data Analysis: Enables detailed analysis of customer interactions for insights and improvements.
  • Sentiment Analysis: Textual data allows for sentiment analysis, helping to gauge customer satisfaction.
  • Trend Analysis: Identifying common issues and trends from transcripts can inform product and service improvements.

Business Meetings

• Accurate Minutes: Provides real-time, accurate minutes of meetings.
  • Automated Summarization: Tools can summarize key points and actions from meeting transcripts.
  • Follow-up Actions: Transcripts ensure that action items are clearly documented and followed up.
• Accessibility: Assists in making meetings accessible to hearing-impaired participants.
  • Live Captions: Real-time transcription provides live captions for participants.
  • Translatable Transcripts: Transcripts can be easily translated into other languages for non-native speakers.
• Searchable Records: Creates searchable records of meetings for future reference.
  • Keyword Search: Allows users to quickly find specific discussions or decisions in meeting transcripts.
  • Knowledge Management: Integrates with knowledge management systems to archive and retrieve meeting content.

Media and Broadcasting

• Live Subtitling: Provides real-time subtitles for live broadcasts.
  • Broadcast Delay Compensation: Ensures that subtitles are synchronized with live audio.
  • Multilingual Support: Supports multiple languages for international broadcasts.
• Content Creation: Facilitates the creation of written content from audio sources.
  • Transcription for Editing: Editors can use transcripts to streamline the video and audio editing process.
  • SEO Optimization: Transcripts can be used to generate searchable text content for SEO purposes.

Streaming Speech-to-Text Solutions in 2024

Here are some leading providers offering robust transcription services:

Picovoice Leopard

• Overview: Picovoice Leopard provides highly accurate streaming speech-to-text services optimized for embedded systems.
  • On-Device Processing: Ensures privacy and reduces latency by processing audio locally.
  • Low Latency: Provides near-instantaneous transcription suitable for real-time applications.
  • Privacy-Preserving: No audio data leaves the device, ensuring maximum privacy.

Azure Speech-to-Text

• Overview: Microsoft’s Azure Speech-to-Text service offers comprehensive transcription capabilities as part of its Azure Cognitive Services suite.
  • Customizable Models: Users can train custom models to improve accuracy for specific terminologies and accents.
  • Real-Time and Batch Transcription: Supports both real-time and batch processing, allowing for flexible use cases.
  • Multi-Language Support: Provides transcription in over 60 languages and dialects.

Krisp Call Center Transcription

• Overview: Krisp’s solution is specifically designed for call centers, offering not only on-device transcription but background noise cancellation and accent localization features as well.
  • Customizable Features: Users can fine-tune the noise cancellation and accent localization to better fit the specific needs of their call centers.
  • On-Device Transcription: Supports on-device transcription, ensuring accurate representation of calls.
  • Background Noise Cancellation: Utilizes advanced AI to filter out background noises, enhancing call clarity and customer experience.
  • Accent Localization: Automatically adjusts to various accents, ensuring clear and accurate transcription regardless of the speaker’s accent.

Krisp’s Transcription Software: Leading the Way

Krisp Call Center Transcription employs noise-robust deep learning algorithms for on-device speech-to-text conversion. Specifically, the process consists of several stages:

Technical Advantages of Krisp for Enterprise Call Centers

• Superior Transcription Accuracy

  • 96% Accuracy: Leveraging cutting-edge AI, Krisp ensures high-quality transcriptions even in noisy environments, boasting a Word Error Rate (WER) of only 4%.

  On-Device Processing

  • Enhanced Security: Krisp’s desktop app processes transcriptions and noise cancellation directly on your device, ensuring sensitive information remains secure and compliant with stringent security standards.

  Unmatched Privacy

  • Real-Time Redaction: Ensures the utmost privacy by redacting Personally Identifiable Information (PII) and Payment Card Information (PCI) in real-time.
  • Private Cloud Storage: Stores transcripts in a private cloud owned by customers, with write-only access, ensuring complete control over data.

  Centralized Solution Across All Platforms

  • Cost Optimization: By centralizing call transcriptions across all platforms, Krisp CCT optimizes costs and simplifies data management.
  • Streamlined Operations: Eliminates the need for multiple transcription services, making data handling more efficient.

  No Additional Integrations Required

  • Effortless Integration: Krisp’s plug-and-play setup integrates seamlessly with major Contact Center as a Service (CCaaS) and Unified Communications as a Service (UCaaS) platforms.
  • Operational Efficiency: Requires no additional configurations, ensuring smooth and secure operations from the start.

Wrapping up

Streaming speech-to-text technology is a game-changer for enterprises, particularly in call centers. It enhances customer service, operational efficiency, and data management. Krisp’s transcription software, with its superior noise cancellation and on-device transcription capabilities, is a standout choice for businesses looking to leverage this technology.

Streaming speech-to-text FAQ

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Understanding Call Center Transcription

Call center transcription involves converting spoken conversations from customer service calls into written text. This transcription can be done in real-time or post-call, and the transcribed text can be used for various purposes such as quality assurance, training, compliance, and analytics. Transcription software automates this process, providing accurate and efficient documentation of customer interactions.

Transcription is not a new concept. It has been used in various fields such as legal, medical, and media for decades. However, its application in call centers has gained significant traction due to the increasing need for detailed records of customer interactions. By transcribing calls, call centers can analyze conversations, monitor agent performance, and ensure compliance with industry regulations.

Why is Transcription Software Essential for Call Centers?

In today’s competitive business environment, call centers need to leverage every tool available to enhance their operations. Transcription software is one such tool that offers several advantages:

Advantage	Description
Improved Customer Experience	By transcribing calls, call centers can better understand customer issues and preferences, leading to more personalized and effective service.
Enhanced Quality Assurance	Transcriptions provide a detailed record of conversations, making it easier to review and assess agent performance.
Compliance and Legal Protection	Transcriptions ensure that all conversations are documented, helping call centers comply with regulatory requirements and protecting against potential legal disputes.
Training and Development	Transcripts can be used as training material for new agents, showcasing real-life examples of customer interactions.
Data Analytics	Transcribed data can be analyzed to identify trends, measure customer satisfaction, and make informed decisions.

Without transcription software, call centers may struggle to maintain accurate records, analyze customer interactions, and ensure high standards of service. The manual transcription process is time-consuming and prone to errors, making automated transcription software a necessity for modern call centers.

Key Features for Call Center Transcription Software

When selecting transcription software for a call center, it is crucial to consider the features that will meet the specific needs of the business. Here are the key features to look for in 2024:

1. Accuracy and Reliability

High accuracy in transcription is essential to ensure that the transcribed text accurately reflects the conversation. Look for software that uses advanced AI and machine learning algorithms to achieve high accuracy rates. Aim for at least a 95% accuracy rate in ideal conditions.

2. Real-Time Transcription

Real-time transcription allows call centers to access transcribed text instantly, enabling immediate action on critical information. This feature is particularly useful for monitoring live calls and providing on-the-spot feedback to agents. The latency should be under 2 seconds for optimal performance, ensuring minimal delay between spoken words and transcribed text.

3. Multi-Language Support

In a globalized market, call centers often deal with customers from diverse linguistic backgrounds. Transcription software should support multiple languages to cater to this diversity. Support for at least 10 major languages and the ability to quickly add new languages as needed can be a significant advantage. Ensure the software uses neural networks trained on diverse datasets to handle various accents and dialects.

4. Integration Capabilities

The software should seamlessly integrate with existing call center systems such as CRM, helpdesk, and communication platforms. This ensures smooth workflow and data synchronization. Look for API compatibility and pre-built connectors for popular systems like Salesforce, Zendesk, and Microsoft Teams to reduce integration time and complexity.

5. Customizable Vocabulary

Call centers often use industry-specific terminology and jargon. Software that allows customization of vocabulary ensures more accurate transcriptions by recognizing these terms. The ability to upload custom dictionaries and train models on specific datasets can improve recognition of unique terms and phrases by up to 20%.

6. Data Security and Compliance

Given the sensitive nature of customer interactions, transcription software must offer robust data security measures. It should comply with relevant regulations such as GDPR, HIPAA, and PCI-DSS to protect customer data. End-to-end encryption, secure cloud storage, and regular security audits are essential features. Ensure the provider has ISO 27001 certification for information security management.

7. Scalability

As call centers grow, the transcription software should be able to scale accordingly. It should handle increased call volumes without compromising performance. Look for solutions that can scale to handle thousands of simultaneous transcriptions with uptime guarantees of 99.9% or higher, ensuring reliability during peak times.

8. Speaker Identification

Identifying different speakers in a conversation is crucial for clarity and accuracy. Look for software that offers reliable speaker identification to distinguish between agents and customers. Advanced models can achieve speaker diarization accuracy rates of over 90%, ensuring clear attribution of each part of the conversation.

9. Analytics and Reporting

Transcription software should provide detailed analytics and reporting features. This includes sentiment analysis, keyword spotting, and trend analysis to help call centers gain insights from transcribed data. Real-time dashboards, customizable reports, and integration with BI tools like Tableau or Power BI can enhance decision-making and strategy development.

10. Ease of Use

The software should have an intuitive interface that is easy for agents and managers to use. Training time should be minimal to ensure quick adoption. Features like drag-and-drop interfaces, contextual help guides, and 24/7 support can reduce the learning curve and improve user satisfaction.

The software should have an intuitive interface that is easy for agents and managers to use. Training time should be minimal to ensure quick adoption.

Krisp: Versatile Transcription Software for Call Centers

Krisp is a versatile and reliable transcription software designed to enhance call center operations and improve customer service. Here’s why Krisp is a top choice for call centers:

Detailed Analysis of Krisp Features

On-Device Processing

• Processes transcriptions and noise cancellation directly on your device.
• Ensures real-time processing with low latency.
• Keeps data secure by not transmitting it to external servers.

Unmatched Privacy

• Decrypts PII and PCI in real-time, storing transcripts securely in a private cloud.
• Meets GDPR and HIPAA privacy regulations.

Superior 96% Accuracy

• Utilizes advanced AI and machine learning algorithms to achieve a Word Error Rate (WER) of only 4%.
• Maintains accuracy across various languages and dialects.

A Single Solution Across All Platforms

• Seamlessly integrates with CRM and call center platforms, including Salesforce and Zendesk.
• Centralizes data management, reducing operational complexity.

No Additional Integrations Required

• Plug-and-play integration with major CCaaS and UCaaS platforms.
• Simplifies the setup process and adapts to various call center environments.

Use Cases Enabled by Krisp Call Center Transcription

Robust Governance and Privacy & Security Measures

Krisp is a powerful tool for modern call centers, offering high accuracy, real-time capabilities, multi-language support, seamless integration, and robust security measures. By leveraging Krisp, call centers can improve efficiency, gain valuable insights, and ensure high-quality customer interactions.

FAQ on Call Center Transcription Software

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This guide will walk you through the all hands meeting meaning, how to run it effectively, and what best practices to use. Moreover, you’ll learn how to utilize an AI meeting assistant to make virtual gatherings productive and engaging and unite employees.

Key Takeaways:

• Also called town halls, all hands meetings are company-wide online or offline gatherings that include employees and managers from all levels.

• A town hall aims to bring company members together to share updates, discuss information and company culture, align goals, celebrate wins, and address concerns or questions all at once.

• An AI meeting assistant designed to eliminate noise, record remote meetings, and automatically transcribe and take notes can make meetings productive, enhance communication and collaboration within companies, and foster a sense of unity.

What Is an All Hands Meeting?

The name is derived from the phrase “all hands on deck,” a signal calling all ship crew members on deck. Specifically, all hands meetings can be online or in-person and occur monthly, quarterly, or annually, which we’ll discuss below.

Importantly, they’re more vital for remote, distributed, or hybrid teams, as they interact face-to-face less often. What’s more, opinions expressed during these strategic symposiums can be game-changers and move things forward.

How do all hands meetings differ from typical team meetings? The first ones more effectively keep the entire company on the same page and are great for companywide announcements. The second ones are more valuable for specific project updates.

What Is the Purpose of an All Hands Meeting?

All hands meetings aim to get everyone on the same page regarding company goals, initiatives, vision, and strategies. After all, departments, teams, and employees can miss the big picture by getting wrapped up in their specific tasks.

But that’s only part of the story. All hands meetings aim to:

• Build unity around business goals and strategies by sharing experiences and discussing roadblocks.

• Reinforces company culture, which can be abstract and hard to grasp. Namely, sharing company values and discussing the behavior of leaders who embody them cultivate a value-driven environment.

• Enable leaders to gather different opinions and ideas to arrive at the best possible conclusion. For example, business advisor Glenn Llopis said, “Your voice can challenge the company’s status quo and cultivate innovation.”

• Allow employees to surface rarely-seen large-scale questions about the company’s operations.

• Enjoy a healthy debate based on different opinions to learn new viewpoints, possibilities, and experiences.

• Enable managers to discover talent and look at employees with a new perspective based on the opinions expressed during meetings.

• Create a positive and supportive company culture by discussing progress,  recognizing achievements, and celebrating milestones.

• Build transparency and honesty by sharing performance updates, challenges, and plans. 

• Let leaders assess the company’s health and make informed decisions through shared feedback and Q&As.  

• Bring together remote employees, ensuring trust and effective communication without frustration. 

• Help quickly spread critical information and adapt strategies in times of crisis or major change. Thus, leaders can proactively address concerns, outline action plans, and manage the situation.

How Often Should a Company Have All Hands Meetings?

Companies usually host monthly, biweekly, or weekly all hands meetings. Precisely, quarterly meetings are typical for companies that aren’t fast-paced. Once decided, the meeting organizer should schedule them as recurring meetings on participants’ calendars.

Smaller companies can host these gatherings weekly to maintain close communication. And larger companies usually hold all hands monthly, as bringing hundreds or thousands of people together at once is challenging.

The good news is that modern conferencing tools help connect large groups more easily. For instance, an AI meeting assistant developed with productivity in mind removes background noise, automates transcriptions during remote meetings, and records them flawlessly.

As a result, hosting an all hands meeting online has become effortless and effective, enabling companies to organize them frequently.

Overall, the frequency depends on whether the company faces rapid changes, prioritizes transparency, and launches projects frequently. For example, companies must share their yearly plans at the start of the year.

Moreover, companies adjust the frequency based on employees’ feedback regarding the effectiveness and impact of these gatherings. So, it’s always good to experiment weekly and monthly to come up with the best solution.

How to Run an All Hands Meeting Effectively?

Leaders are often worried about running meetings effectively so employees can speak up and share ideas without confusion or frustration.

So, how can you, as a leader, invite participation and expect proactive responses? Moreover, what if opposing opinions lead to conflict, leaving no space for consensus?

For example, I remember a company hosting dry, data-heavy, and disengaging all hands meetings. And when leaders shifted those gatherings to a more interactive format, focusing on storytelling rather than statistics, they witnessed a 30% increase in employee engagement scores.

They created segments like “Behind the Scenes,” in which different teams shared insights into their daily work. As a result, the company became more transparent and exciting to all employees.

Now, let’s dig deeper to learn to hold all hands meetings effectively.

Prepare for Your Meeting

Step 1: Create Your Meeting Agenda

Consider an agenda like this one that includes:

• Welcome & icebreaker (5-7 mins)
• Company updates (15 mins)
• Departmental highlights (20 mins)
• Special topics (20 mins)
• Guest speaker or special presentation (10 mins)
• Q&A session (15 mins)
• Recognition & awards (10 minutes)
• Closing & feedback (5 mins).

Step 2: Change the Meeting Venues

For instance, choose a large conference room, auditorium, or fun off-site space. However, ensure it comfortably accommodates the entire staff and supports technology for presentations and remote participation.

Step 3: Invite All Relevant Attendees

The all hands meeting attendees include:

• The executive team
• Chief financial officer (CFO)
• Chief operating officer (COO) and other C-suite executives
• Department heads and managers
• All employees
• Remote workers.

Step 4: Survey the Employees

Send out a survey a week before the meeting to gather questions and topics of interest. Because this helps gather input on topics employees are interested in discussing.

Step 5: Go Through a Dry Run

Run a technical rehearsal to avoid hiccups, especially when using new technology or formats.

During the All Hands Meeting

Step 1: Start Strong

Kick off with a compelling story or a valuable company milestone or celebrate accomplishments since the last gathering. This also applies to nonbusiness achievements, such as marriage and milestones. Also, consider starting with a meeting icebreaker.

Step 2: Keep the Meeting Moving 

• Include informative updates
• Incorporate live polls or real-time feedback
• Give everyone a chance to ask questions 
• Ask employees to submit questions or discussion topics in advance
• Listen to diverse groups of presenters with varying ideas
• Let each department discuss its news and achievements or project updates
• Plan five-to-ten-minute small group discussions

Step 3: Communicate Clearly

• Communicate your message through compelling visuals, such as slides and videos, to make your speech memorable.

• Ensure an all hands meeting environment of mutual respect so participants can engage in dialogue without conflicts. Interestingly, American educator Stephen Covey wrote that members should be encouraged to understand one another first and then expect others to understand them.

• Invite an expert or a coach to get a fresh perspective and enhance engagement.

Step 4: Ensure Post-Meeting Follow-up

• Distribute a recap with a video recording, main takeaways, and action items.
• Solicit feedback for continuous feedback: What worked? What didn’t? 
• Facilitate post-meeting follow-up using an AI meeting assistant designed to automate transcription and note-taking.

Krisp Connects People & Boosts Productivity of All Hands Meeting

“The future of human sociality lies in understanding and consequently shaping online interaction,” said psychologists Lieberman & Schroeder.

And AI meeting assistant Krisp is committed to making your online all hands meeting productive, effective, dynamic, and effortless, enhancing virtual communication and helping people connect better.

Let me show you how:

• Krisp’s AI Meeting Transcriptions help people unite and foster team identification: This automated, multilingual transcription feature transcribes calls and meetings in real time and with 96% accuracy.

Thus, it enables participants to discuss core issues and share ideas instead of focusing on transcribing or creating an all hands meeting template. Additionally, it helps manage the overwhelming amount of meeting data, which is especially critical for larger companies.

• Krisp’s AI Meeting Notes & Summaries keep members in sync: This feature generates meeting notes, summaries, and action items by reflecting key meeting elements.

With the essential meeting information at hand, team members become more organized, enthusiastic, and driven to accomplish their goals.

• Krisp’s Meeting Recording creates transparency and accessibility: This feature automatically captures all hands meetings with high-quality audio. Importantly, it’s compatible with any virtual conferencing app or platform, including Zoom and Google Meet.

Thus, this feature transforms your meeting into a memorable source of information that you constantly revisit to review. Additionally, it turns your meetings into more accessible, open, and actionable resources to boost productivity and collaboration.

• Krisp’s AI Noise Cancellation eliminates distractions from online meetings: This feature removes background noises, voices, and echoes in real time.

Specifically, Krisp’s advanced Voice AI technology ensures best-in-class audio clarity to let you engage in meetings more productively and effectively. So you can focus on what matters most during online gatherings.

All Hands Meeting Best Practices

All hands meeting best practices offer working standards or guidelines for good outcomes. Let’s get started.

1. Timing is Everything: Decide your meeting frequency and create a schedule that respects everyone’s time. And we’ve already discussed the frequency above. What about the best time of day? Well, mid-morning or late afternoon typically sees peak engagement.

2. Avoid Mundane Meetings: According to a Harvard Business Review study of over the past 50+ years, meetings are taking longer hours and becoming more frequent. Did you know employees shy away from long and boring meetings? So, maintain a strict agenda, allocate specific times for each segment, and prepare concise presentations.

3. Keep It Interactive: People want to avoid sitting through a monologue. How can you turn an all hands meeting into a two-way conversation? Use live polls, Q&A sessions, and even interactive quizzes to keep the energy up. And avoid overshadowing introverts.

4. Streamline Your Agenda: An all hands meeting without a clear agenda is like a ship without a rudder going off course. Moreover, prioritize updates that affect the entire company. Additionally, include finance, HR, major project milestones, and strategic pivots.

5. Celebrate Achievements: Here’s something you’ll want to remember: recognition fuels motivation. So, take time to shine a spotlight on team and individual accomplishments. Maybe your sales team has surpassed its quarterly targets. And what about the development team’s release of a new feature ahead of schedule?

6. Address the Elephants in the Room: Transparency builds trust, prevents misinformation, and keeps everyone on the same page. So, are there rumors about funding or layoffs? Address them head-on.

Final Word

The goal of an all hands meeting is to keep every team member informed, engaged, and aligned with the company’s goals, mission, and culture. When properly executed, these meetings foster a united and motivated workforce.

The guide above discusses how to make all hands meetings flexible, effective, and innovative to inspire and unite the entire team. And AI meeting assistants like Krisp can significantly enhance meeting productivity, engagement, and effectiveness.

Frequently Asked Questions

The post All Hands Meeting: A Step-by-Step Guide appeared first on Krisp.

On-device transcription software processes speech-to-text conversions directly on the device, without relying on cloud-based services. This method leverages local computational power to perform transcription tasks, ensuring data is processed quickly and securely.

The software uses advanced machine learning algorithms and neural networks to recognize and transcribe speech in real time. Utilizing the device’s hardware minimizes latency and enhances the accuracy of transcriptions.

Benefits of On-Device Transcription in Call Centers

Call centers handle vast amounts of data daily, making efficient transcription crucial. On-device transcription software addresses several key areas to optimize call center operations Main advantages of speech-to-text solutions include:

Enhanced Privacy and Security: Security is a major concern in the call center industry, especially when handling sensitive customer information. On-device transcription ensures that audio stays on the device, significantly lowering the risk of data breaches. This approach complies seamlessly with strict data protection regulations, assuring both call centers and their customers.
Improved Speed: Real-time processing eliminates delays associated with data transfer to and from cloud servers. Also, this feature can be a game-changer, enabling agents to see a real-time transcript of the call.
Cost-Effectiveness: The most immediate benefit of on-device transcription is cost savings. Traditional cloud transcription services are very expensive due to the costs associated with audio data transmission and processing on remote servers. On-device transcription, however, leverages the processing power of the agent’s device, leading to a significant reduction in these costs.

What is Behind On-Device Transcription Technology?

On-device transcription technology is grounded in advanced artificial intelligence and machine learning. Here’s a detailed look at how it works:

1. Speech Recognition Algorithms: These algorithms convert spoken language into text by analyzing audio signals. They break down the audio into smaller units called phonemes, which are then matched with known language patterns.
2. Natural Language Processing (NLP): NLP techniques help the software understand context, grammar, and syntax, improving the accuracy of transcriptions.
3. Acoustic Models: These models analyze the properties of sound waves to distinguish between different words and sounds, even in noisy environments.
4. Language Models: Language models predict the next word in a sequence, helping to correct errors and improve transcription quality.

Overcoming Historical Challenges of On-Device Transcription in Call Centers

Historically, on-device transcription wasn’t an option for several reasons:

Hardware Limitations

The CPU requirements for on-device transcription could exceed the capabilities of existing hardware in call centers, requiring costly upgrades. However, this challenge is being rapidly addressed by two factors:

• Speech-to-text technologies have become significantly more efficient in terms of CPU and memory requirements, making them capable of running locally.
• The influx of AI-powered laptops and workstations from Intel, AMD, and Qualcomm designed to handle such tasks efficiently.

Integration Challenges

Historically, integrating on-device transcription with various call center systems and software was complex, requiring significant technical effort and resources. However, with the integration of cloud systems in call centers, this is no longer a challenge. The transcriptions and recordings generated on agents’ devices can be easily uploaded to AWS, Google, Azure, or other cloud storage and then fed into Call Center AI solutions such as CallMiner, Observe AI, AWS Connect, NICE, etc.

Low Transcription Quality

Historically, on-device solutions yielded lower-quality transcriptions since only small models could be deployed on the device, and there was limited access to the latest AI models and updates available in cloud-based systems. However, progress in Speech-to-text models and the availability of better CPUs makes it possible to successfully deploy and run high-quality efficient models on-device.

Comparing On-Device and Cloud-Based Transcription for Call Centers

To better understand the benefits of on-device transcription, let’s compare it to cloud-based transcription services in a few key areas.
This comparison will highlight why on-device solutions are becoming increasingly favored in the industry.

Feature	On-Device Transcription	Cloud-Based Transcription
Privacy	High – Data processed locally	Medium – Data transmitted to the cloud
Speed	High – Real-time processing	Variable – Dependent on internet speed
Cost	Lower ongoing costs	Higher ongoing costs due to service fees
Scalability	Variable – Dependent on device capability	Highly scalable with cloud resources
Reliability	High – Less dependent on the internet	Variable – Dependent on internet connectivity

Choose your On-Device Transcription Software

Here are six top on-device transcription software options that can streamline your operations:

1. Krisp

Krisp offers powerful on-device transcription capabilities that seamlessly convert call conversations into text. With its robust noise-canceling technology, Krisp ensures that only clear and relevant speech is transcribed, making it a top choice for call centers looking for reliable and accurate transcriptions.

2. Otter.ai

Otter.ai is renowned for its advanced AI-driven transcription services. It provides real-time transcription and features collaborative tools for team-based environments, making it an excellent fit for call centers that require quick and precise transcriptions.

3. Sonix

Sonix offers fast and accurate transcription services with a focus on security and data privacy. It supports multiple languages and provides powerful editing tools to refine transcriptions, which is beneficial for call centers handling international clients.

4. Trint

Trint utilizes AI to deliver highly accurate transcriptions that can be edited and shared within the team. Its robust platform supports integrations with various CRM systems, ensuring seamless workflow integration for call centers.

5. Rev

Rev provides on-device transcription with a strong emphasis on accuracy and speed. It offers user-friendly tools to manage and edit transcripts, making it a reliable choice for call centers that require quick turnaround times.

6. Descript

Descript is a versatile transcription software that combines transcription with video and audio editing features. Its unique approach allows call centers to not only transcribe calls but also create and edit media content, making it a multifunctional tool for various needs.

Krisp: Best On-Device Call Center Transcription Software

As we conclude our exploration of on-device transcription for call centers, it’s clear that selecting the right tool is crucial. Indeed, Krisp stands out, providing unmatched accuracy, usability, and integration.

With Krisp, call centers can enjoy:

• Superior Transcription Accuracy 96% : Leveraging cutting-edge AI, Krisp ensures high-quality transcriptions, even in noisy environments. Furthermore, Krisp CCT delivers unmatched transcription accuracy with a WER (Word Error Rate) of only 4%.
• On Device Processing: Krisp’s desktop app processes transcriptions and noise cancellation directly on your device, thereby keeping sensitive info secure and compliant with strict security standards.
• Unmatched privacy: Krisp ensures the utmost privacy by redacting PII and PCI in real-time, storing transcripts in a private cloud owned by customers with write-only access.
• A single solution across all platforms: By centralizing call transcriptions across all platforms, Krisp CCT optimizes costs and simplifies data management, eliminating the need for multiple transcription services.
• No additional integrations required: Krisp’s plug-and-play setup integrates effortlessly with major CCaaS and UCaaS platforms. Requiring no additional configurations, Krisp ensures your operations run smoothly and securely.

How Krisp Call Center Transcription works technically

Krisp Call Center Transcription employs noise-robust deep learning algorithms for real-time on-device speech-to-text conversion. Specifically, the process consists of several stages:

The post On-Device Transcription Software in Call Centers: A True Game Changer appeared first on Krisp.

What if staff training isn’t the only solution to navigating through different accents? Imagine a world where technology could effortlessly bridge the gap. This is where advanced software solutions come into play and we’ll discuss it in this article.

Accent Barriers at Call Centers

First off, let’s tackle the elephant in the room: accent barriers. Call centers, especially those serving international clients, encounter a wide variety of accents daily. This diversity, while enriching, can sometimes hinder clear communication. Misunderstandings arising from accent differences can lead to frustration on both ends of the line, potentially affecting customer satisfaction (CSAT) scores and, by extension, the reputation of the business.

Accent training in call centers aims to minimize these barriers, ensuring agents can communicate effectively with a global clientele. This training often involves accent neutralization—equipping agents with a more universally understandable accent—and accent comprehension, enhancing their ability to understand the diverse accents of callers.

Traditional vs Software Solution Accent Training Methods

Aspect	Traditional Training	Software Solutions (Krisp)
Speed of Implementation	Slow: Requires setup and training periods.	Instant: Real-time accent modification.
Cost	Higher: Includes trainer, materials, and venue costs.	Lower: Primarily subscription or purchase cost.
Efficiency	Variable: Dependent on training quality and learning pace.	High: Consistent and immediate accent clarity.
Scalability	Limited: More resources needed for more agents.	Easy: Quickly scalable across any team size.
Cognitive Load on Agents	High: Constant focus on speech can detract from service.	Reduced: Agents focus more on service, less on speech.
Privacy and Security	Controlled internally.	Depends on the software’s data policies.
Customer Satisfaction Impact	Gradual: Improvements take time.	Immediate: Enhances clarity and comprehension quickly.

Call Center Accent Training Traditional Methods

Accent training methodologies in call centers are as diverse as the accents themselves. They range from traditional in-person training sessions to innovative digital platforms that use speech recognition and artificial intelligence to tailor training to individual needs. These methods typically include:

Problems that Accent Localization Solves at Call Centers

Accent neutralization, or accent reduction, aims to make an agent’s accent more understandable to a wide range of callers without erasing their linguistic identity. This approach addresses several key issues in call centers:

• Improved Customer Satisfaction: Clearer communication leads to more effective resolutions of customer queries, directly impacting CSAT scores.
• Reduced Miscommunication: By minimizing accent-related misunderstandings, call centers can operate more efficiently, with fewer calls needing escalation.
• Enhanced Global Reach: Agents with neutralized accents can communicate more effectively with a global audience, expanding the potential customer base for the business.

Krisp AI Accent Localization: The Innovative Edge in Call Center Communication

Call center accent training has long been a staple of the industry, aiming to forge clear lines of communication across diverse customer bases. However, the evolution of AI technologies presents new avenues to streamline this process. Krisp AI Accent Localization is at the forefront of this revolution, offering real-time accent conversion to enhance communication effectiveness.

Accent Localization in Action with Krisp

Krisp’s accent localization feature dynamically modifies an agent’s accent during a call. This ensures the customer hears the agent’s voice in an accent that is familiar and easily understandable, thereby reducing miscommunication and improving customer satisfaction. Below is a detailed table showcasing the key features of Krisp’s AI Accent Localization:

Experience the magic of Krisp’s Accent Localization

Why Choose AI Over Traditional Training?

While traditional training programs focus on long-term accent modification, AI-driven solutions like Krisp offer instant and dynamic adjustments. Here’s why this is a game-changer for call centers.

Advantage	Description
Instant Implementation	Unlike conventional training that takes weeks or months, AI accent localization works in real-time.
Reduced Training Time and Cost	AI eliminates the extensive hours and significant costs associated with ongoing accent training programs.
Cognitive Load Reduction	Agents can focus on customer service rather than the constant self-monitoring of their speech.
Scalability	Software like Krisp can be quickly rolled out across teams of any size, providing immediate benefits.

Improving Agent Experience and Broadening the Hiring Pool

The use of AI for accent localization isn’t just about customer experience; it’s also about enhancing the work life of call center agents. Krisp’s technology reduces the cognitive load on agents, who no longer need to focus on maintaining a neutral accent. This improves job satisfaction and retention rates.

Furthermore, the AI solution expands the hiring pool. Call centers can focus on hiring based on skill and fit rather than accent proficiency. This not only supports diversity and inclusion initiatives but also taps into a broader talent pool.

Conclusion: The Role of AI in the Future of Call Centers

In wrapping up, it’s clear that the landscape of call center operations is on the cusp of a significant evolution. As AI-driven technologies, such as advanced accent neutralization software, take the lead, they herald a departure from the age-old reliance on intensive accent training.

This transition is not just about adopting new tools; it’s a transformative shift towards harnessing technology to ensure every customer interaction is marked by clarity and understanding. In essence, we’re stepping into a future where global communication barriers are effortlessly navigated, thanks to the innovative solutions brought forth by AI.

FAQ on Call Center Accent Training

The post Call Center Accent Training: Breaking The Language Barriers appeared first on Krisp.

Managing conversations well is crucial in busy call centers, where every call matters. Have you ever hung up after talking to a customer and wished you could remember everything that was said? Maybe you think you could have explained things better, or you can’t quite recall an important detail they mentioned. Writing down what was said on the phone, or call transcriptions, can be super helpful.

Nowadays, keeping a written record of phone calls is a big part of giving great customer service. These written records can greatly help anyone who works in a call center, dealing with customers all day.

Indeed, having transcription software in place is like having a super-efficient, never-tiring assistant who notes down everything for you.

How Call Center Transcription Works?

The magic of transcription software is its ability to capture and convert every spoken word of the call into text. This process not only serves as a real-time documentation tool but also as a database for future reference and analysis.

Here’s a closer look at the technology and importance of call transcription in today’s call centers:

Voice Recognition Technology	The software utilizes advanced voice recognition algorithms to accurately transcribe spoken language into text, regardless of accents or speech nuances.
Real-Time Transcription	As a conversation unfolds, the software transcribes the dialogue in real time, allowing for immediate review or action if necessary.
Data Analysis and Insights	The transcribed texts serve as a valuable resource for analyzing customer interactions, identifying common issues, and uncovering insights into customer behavior and preferences.
Compliance and Quality Assurance	With every call documented, call centers can easily comply with legal requirements and perform quality control checks to ensure high service standards.

By transforming voice into actionable text, call center transcription software not only enhances operational efficiency but also provides a platform for deeper customer understanding and engagement.

Why Do You Need Transcription Software in Your Call Center?

In reality, use of the transcription software in call centers is far from a luxury—it’s a strategic necessity. Here are several compelling reasons why integrating this technology is crucial for your operation:

Undoubtedly, call center transcription software is about unlocking the full potential of every customer interaction.

Krisp: Best Call Center Transcription Software

As we conclude our exploration of call center transcription software, it’s clear that selecting the right tool is crucial. Indeed, Krisp stands out, providing unmatched accuracy, usability, and integration.

With Krisp, call centers can enjoy:

• Superior Transcription Accuracy 96% : Leveraging cutting-edge AI, Krisp ensures high-quality transcriptions, even in noisy environments. Furthermore, Krisp CCT delivers unmatched transcription accuracy with a WER (Word Error Rate) of only 4%.
• On Device Processing: Krisp’s desktop app processes transcriptions and noise cancellation directly on your device, thereby keeping sensitive info secure and compliant with strict security standards.
• Unmatched privacy: Krisp ensures the utmost privacy by redacting PII and PCI in real-time, storing transcripts in a private cloud owned by customers with write-only access.
• A single solution across all platforms: By centralizing call transcriptions across all platforms, Krisp CCT optimizes costs and simplifies data management, eliminating the need for multiple transcription services.
• No additional integrations required: Krisp’s plug-and-play setup integrates effortlessly with major CCaaS and UCaaS platforms. Requiring no additional configurations, Krisp ensures your operations run smoothly and securely.

How Krisp Call Center Transcription works technically

Krisp Call Center Transcription employs noise-robust deep learning algorithms for real-time on-device speech-to-text conversion. Specifically, the process consists of several stages:

See Krisp Call Center Transcription in action

Summing up

Summing up, the introduction of Krisp Call Center Transcription Software into your operations isn’t just a leap in technology—it’s a strategic masterstroke. This powerful tool not only provides quick and accurate transcriptions of customer calls but also propels your service quality to new heights, streamlines intricate data management, and cultivates deeper customer connections.

Here are the key use cases where Krisp takes center stage in enhancing call center performance:

• Enhancing Call Center Efficiency: Krisp catapults your BPO’s productivity forward. It brings quality control to the forefront, enriches training and coaching sessions, sharpens sales tactics, and fine-tunes key performance metrics, altogether fostering a more robust operation.
• Ensuring Compliance and Legal Integrity: With Krisp, your adherence to regulatory compliance and industry standards is solidified. It serves as an indispensable asset in legal matters, providing evidence when needed and reinforcing data privacy practices to maintain your legal standing.
• Enabling Customer Intel Gathering: Krisp simplifies the collection and analysis of customer data. It helps in pinpointing actionable insights, understanding customer needs more profoundly, and capturing valuable feedback for future offerings.
• Fortifying Fraud Detection: The software is also an ally in safeguarding your enterprise. It spots suspicious patterns, helps to head off potential data breaches, and bolsters your strategies against fraudulent activities, ensuring that your business and customers remain secure.

In sum, Krisp as your call center transcription software isn’t just a choice. It’s a strategic decision that empowers you to meet the challenges of today’s digital and fast-paced customer service world with confidence and savvy.

FAQ on Call Center Transcription Software

The post Call Center Transcription Software: The Ultimate Guide appeared first on Krisp.

Accent refers to the distinctive way in which a group of people pronounce words, influenced by their region, country, or social background. In broad terms, English accents can be categorized into major groups such as British, American, Australian, South African, and Indian among others. 

Accents can often be a barrier to communication, affecting the clarity and comprehension of speech. Differences in pronunciation, intonation, and rhythm can lead to misunderstandings. 

While the importance of this topic goes beyond call centers, our primary focus is this industry.

Offshore expansion and accented speech in call centers

The call center industry in the United States has experienced substantial growth, with a noticeable surge in the creation of new jobs from 2020-onward, both on-shore and globally.

In 2021, many US based call centers expanded their footprints thanks to the pandemic-fueled adoption of remote work, but growth slowed substantially in 2022. Inflated salaries and limited resources drove call centers to deepen their offshore operations, both in existing and new geographies.

There are several strong incentives for businesses to expand call centers operations to off-shore locations, including:

• Cost savings: Labor costs in offshore locations such as India, the Philippines, and Eastern Europe are up to 70% lower than in the United States.
• Access to diverse talent pools: Offshoring enables access to a diverse talent pool, often with multilingual capabilities, facilitating a more comprehensive customer support service.
• 24/7 coverage: Time zone differences allow for 24/7 coverage, enhancing operational continuity.

However, offshore operations come with a cost. One major challenge offshore call centers face is decreased language comprehension. Accents, varying fluency levels, cultural nuances and inherent biases lead to misunderstandings and frustration among customers. 

According to Reuters, as many as 65% of customers have cited difficulties in understanding offshore agents due to language-related issues. Over a third of consumers say working with US-based agents is most important to them when contacting an organization.

Ways accents create challenges in call centers

While the world celebrates global and diverse workforces at large, research shows that misalignment of native language backgrounds between speakers leads to a lack of comprehension and inefficient communication. 

• Longer calls: Thick accents contribute to comprehension difficulties, causing higher average handle time (AHT) and also lower first call resolutions (FCR).
  According to ContactBabel’s “2024 US Contact Center Decision Maker’s Guide” the cost of mishearing and repetition per year for a 250-seat contact center exceeds $155,000 per year.
  
• Decreased customer satisfaction: Language barriers are among the primary contributors to lower customer satisfaction scores within off-shore call centers. According to ContactBabel, 35% of consumers say working with US-based call center agents is most important to them when contacting an organization.
• High agent attrition rates: Decreased customer satisfaction and increased escalations create high stress for agents, in turn decreasing agent morale. The result is higher employee turnover rates and short-term disability claims. In 2023, US contact centers saw an average annual agent attrition rate of 31%, according to The US Contact Center Decision Makers’ Guide to Agent Engagement and Empowerment.
• Increased onboarding costs: The need for specialized training programs to address language and cultural nuances further adds to onboarding costs. 
• Limited talent pool: Finding individuals who meet the required linguistic criteria within the available talent pool is challenging. The competitive demand for specialized language skills leads to increased recruitment costs. 

How do call centers mitigate accent challenges today?

Training

Accent neutralization training is used as a solution to improve communication clarity in these environments. Call Centers invest in weeks-long accent neutralization training as part of agent onboarding and ongoing improvement. Depending on  geography, duration, and training method, training costs can run $500-$1500 per agent during onboarding. The effectiveness of these training programs can be limited due to the inherent challenges in altering long-established accent habits. So, call centers may find it necessary to temporarily remove agents from their operational roles for further retraining, incurring additional costs in the process.

Limited geography for expansion

Call centers limit their site selection to regions and countries where accents of the available talent pool is considered to be more neutral to the customer’s native language, sacrificing locations that would be more cost-effective.

Enter AI-Powered Accent Localization

Recent advancements in Artificial Intelligence have introduced new accent localization technology. This technology leverages AI to translate source accents to targets accent in real-time, with the click of a button. While the technologies in production don’t support multiple accents in parallel, over time this will be solved as well.

State of the Art AI Accent Localization Demo

Below is the evolution of Krisp’s AI Accent Localization technology over the past 2 years.

This innovation is revolutionary for call centers as it eliminates the need for difficult and expensive training and increases the talent pool worldwide, providing immediate scalability for offshore operations.

It’s also highly convenient for agents and reduces the cognitive load and stress they have today. This translates to decreased short-term disability claims and attrition rates, and overall improved agent experience.

Deploying AI Accent Localization in the call center

There are various ways AI Accent Localization can be integrated into a call center’s tech stack.

It can be embedded into a call center’s existing CX software (e.g. CCaaS and UCaaS) or installed as a separate application on the agent’s machine (e.g. Krisp).

Currently, there are no CX solutions in market with accent localization capabilities, leaving the latter as the only possible path forward for call centers looking to leverage this technology today.

Applications like Krisp have accent localization built in their offerings. 

These applications are on-device, meaning they sit locally on the agent’s machine. They support all CX software platforms out of the box since they are installed as a virtual microphone and speaker. 

AI runs on an agent’s device so there is no additional load on the network.

The deployment and management can be done remotely, and at scale, from the admin dashboard.

Challenges of building AI Accent Localization technology

At a fundamental level, speech can be divided into 4 parts: voice, text, prosody and accent.

Accents can be divided into 4 parts as well – phoneme, intonation, stress and rhythm.

In order to localize or translate an accent, three of these parts must be changed – phoneme pronunciation, intonation, and stress. Doing this in real-time is an extremely difficult technical problem.

While there are numerous technical challenges in building this technology, we will focus on eight majors.

1. Data Collection
2. Speech Synthesis
3. Low Latency
4. Background Noises and Voices
5. Acoustic Conditions
6. Maintaining Correct Intonation
7. Maintaining Speaker’s Voice
8. Wrong Pronunciations

Let’s discuss them individually.

1) Data collection

Collecting accented speech data is a tough process. The data must be highly representative of different dialects spoken in the source language. Also, it should cover various voices, age groups, speaking rates, prosody, and emotion variations. For call centers, it is preferable to have natural conversational speech samples with rich vocabulary targeted for the use case.

There are two options: buy ready data or record and capture the data in-house. In practice, both can be done in parallel.

An ideal dataset would consist of thousands of hours of speech where source accent utterance is mapped to each target accent utterance and aligned with it accurately. 

However, getting precise alignment is exceedingly challenging due to variations in the duration of phoneme pronunciations. Nonetheless, improved alignment accuracy contributes to superior results.

2) Speech synthesis

The speech synthesis part of the model, which is sometimes referred to as the vocoder algorithm in research, should produce a high-quality, natural-sounding speech waveform.  It is expected to sound closer to the target accent, have high intelligibility, be low-latency, convey natural emotions and intonation, be robust against noise and background voices, and be compatible with various acoustic environments.

3) Low latency

As studies by the International Telecommunication Union show (G.114 recommendation), speech transmission maintains acceptable quality during real-time communication if the one-way delay is less than approximately 300 ms. Therefore, the latency of the end-to-end accent localization system should be within that range to ensure it does not impact the quality of real-time conversation.

There are two ways to run this technology: locally or in the cloud. While both have theoretical advantages, in practice, more systems with similar characteristics (e.g. AI-powered noise cancellation, voice conversion, etc.) have been successfully deployed locally. This is mostly due to hard requirements around latency and scale.

To be able to run locally, the end-to-end neural network must be small and highly optimized, which requires significant engineering resources.

4) Background noise and voices

Having a sophisticated noise cancellation system is crucial for this Voice AI technology. Otherwise, the speech synthesizing model will generate unwanted artifacts.

Not only should it eliminate the input background noise but also the input background voices. Any sound that is not the speaker’s voice must be suppressed.

This is especially important in call center environments where multiple agents sit in close proximity to each other, serving multiple customers simultaneously over the phone. 

Detecting and filtering out other human voices is a very difficult problem. As of this writing, to our knowledge, there is only one system doing it properly today – Krisp’s AI Noise Cancellation technology.

5) Acoustic conditions

Acoustic conditions differ for call center agents. The sheer volume of combinations of device microphones and room setups (accountable for room echo) makes it very difficult to design a robust system against such input variations. 

6) Maintaining the speaker’s intonation

Not transferring the speaker’s intonation in the generated speech will result in a robotic speech that sounds worse than the original. 

Krisp addressed this issue by developing an algorithm capturing input speaker’s intonation details in real-time and leveraging this information in the synthesized speech. Solving this challenging problem allowed us to increase the naturalness of the generated speech.  

7) Maintaining the speaker’s voice

It is desirable to maintain the speaker’s vocal characteristics (e.g., formants, timbre) while generating output speech. This is a major challenge and one potential solution is designing the speech synthesis component so that it generates speech conditioned on the input speaker’s voice ‘fingerprint’ – a special vector encoding a unique acoustic representation of an individual’s voice.

8) Wrong pronunciations

Mispronounced words can be difficult to correct in real-time, as the general setup would require separate automatic speech recognition and language modeling blocks, which introduce significant algorithmic delays and fail to meet the low latency criterion.

3 technical approaches to AI Accent Localization

Approach 1: Speech → STT → Speech

One approach to accent localization involves applying Speech-to-Text (STT) to the input speech and subsequently utilizing Text-to-Speech (TTS) algorithms to synthesize the target speech. 

This approach is relatively straightforward and involves common technologies like STT and TTS, making it conceptually simple to implement. 

STT and TTS are well-established, with existing solutions and tools readily available. 

Integration into the algorithm can leverage these technologies effectively. These represent the strengths of the method, yet it is not without its drawbacks. There are 3 of them:

• The difficulty of having accent-robust STT with a very low word error rate.
• The TTS algorithm must possess capabilities to manage emotions, intonation, and speaking rate, which should come from original accented input and produce speech that sounds natural.
• Algorithmic delay within the STT plus TTS pipeline may fall short of meeting the demands of real-time communication.

Approach 2: Speech → Phoneme → Speech

First, let’s define what a phoneme is. A phoneme is the smallest unit of sound in a language that can distinguish words from each other. It is an abstract concept used in linguistics to understand how language sounds function to encode meaning. Different languages have different sets of phonemes; the number of phonemes in a language can vary widely, from as few as 11 to over 100. Phonemes themselves do not have inherent meaning but work within the system of a language to create meaningful distinctions between words. For example, the English phonemes /p/ and /b/ differentiate the words “pat” and “bat.”

The objective is to first map the source speech to a phonetic representation, then map the result to the target speech’s phonetic representation (content), and then synthesize the target speech from it.

This approach enables the achievement of comparatively smaller delays than Approach 1. However, it faces the challenge of generating natural-sounding speech output, and reliance solely on phoneme information is insufficient for accurately reconstructing the target speech. To address this issue, the model should also extract additional features such as speaking rate, emotions, loudness, and vocal characteristics. These features should then be integrated with the target speech content to synthesize the target speech based on these attributes.

Approach 3: Speech → Speech

Another approach is to create parallel data using deep learning or digital signal processing techniques. This entails generating a native target-accent sounding output for each accented speech input, maintaining consistent emotions, naturalness, and vocal characteristics, and achieving an ideal frame-by-frame alignment with the input data. 

If high-quality parallel data are available, the accent localization model can be implemented as a single neural network algorithm trained to directly map input accented speech to target native speech.

The biggest challenge of this approach is obtaining high-quality parallel data.The quality of the final model directly depends on the quality of parallel data. 

Another drawback is the lack of integrated explicit control over speech characteristics, such as intonation, voice, or loudness. Without this control, the model may fail to accurately learn these important aspects.

How to measure the quality AI Accent Localization output

High-quality output of accent localization technology should:

1. Be intelligible
2. Have little or no accentedness (the degree of deviation from the native accent)
3. Sound natural

To evaluate these quality features, we use the following objective metrics: 

• Word Error Rate (WER)
• Phoneme Error Rate (PER)
• Naturalness prediction

Word Error Rate (WER)

WER is a crucial metric used to assess STT systems’ accuracy. It quantifies the word level errors of predicted transcription compared to a reference transcription. 

To compute WER we use a high-quality STT system on generated speech from test audios that come with predefined transcripts. 

The evaluation process is the following:

• The test set is processed through the candidate accent localization (AL) model to obtain the converted speech samples.
• These converted speech samples are then fed into the STT system to generate the predicted transcriptions.
• WER is calculated using the predicted and the reference texts.

The assumption in this methodology is that a model demonstrating better intelligibility will have a lower WER score.

Phoneme Error Rate (PER)

The AL model may retain some aspects of the original accent in the converted speech, notably in the pronunciation of phonemes. Given that state-of-the-art STT systems are designed to be robust to various accents, they might still achieve low WER scores even when the speech exhibits accented characteristics. 

To identify phonetic mistakes, we employ the Phoneme Error Rate (PER) as a more suitable metric than WER. PER is calculated in a manner similar to WER, focusing on phoneme errors in the transcription, rather than word-level errors.

For PER calculation, a high-quality phoneme recognition model is used, such as the one available at https://huggingface.co/facebook/wav2vec2-xlsr-53-espeak-cv-ft. The evaluation process is as follows:

• The test set is processed by the candidate AL model to produce the converted speech samples.
• These converted speech samples are fed into the phoneme recognition system to obtain the predicted phonetic transcriptions.
• PER is calculated using predicted and reference phonetic transcriptions.

This method addresses the phonetic precision of the AL model to a certain extent.

Naturalness Prediction

To assess the naturalness of generated speech, one common method involves conducting subjective listening tests. In these tests, listeners are asked to rate the speech samples on a 5-point scale, where 1 denotes very robotic speech and 5 denotes highly natural speech. 

The average of these ratings, known as the Mean Opinion Score (MOS), serves as the naturalness score for the given sample.

In addition to subjective evaluations, obtaining an objective measure of speech naturalness is also feasible. It is a distinct research direction—predicting the naturalness of generated speech using AI. Models in this domain are developed using large datasets comprised of subjective listening assessments of the naturalness of generated speech (obtained from various speech-generating systems like text-to-speech, voice conversion, etc). 

These models are designed to predict the MOS score for a speech sample based on its characteristics. Developing such models is a great challenge and remains an active area of research. Therefore, one should be careful when using these models to predict naturalness. Notable examples include the self-supervised learned MOS predictor and NISQA, which represent significant advances in this field.

In addition to objective metrics mentioned above, we conduct subjective listening tests and calculate objective scores using MOS predictors. We also manually examine the quality of these objective assessments. This approach enables a thorough analysis of the naturalness of our AL models, ensuring a well-rounded evaluation of their performance.

AI Accent Localization model training and inference

The following diagrams show how the training and inference are organized.

AI Training

AI Inference

Closing

In navigating the complexities of global call center operations, AI Accent Localization technology is a disruptive innovation, primed to bridge language barriers and elevate customer service while expanding talent pools, reducing costs, and revolutionizing CX.

References

1. https://www.smartcommunications.com/resources/news/benchmark-report-2023-2/
2. https://info.siteselectiongroup.com/blog/site-selection-group-releases-2023-global-call-center-location-trend-report 
3. https://www.siteselectiongroup.com/whitepapers 
4. https://www.reuters.com/article/idUSTRE5AN37C/ 

The post Deep Dive: AI’s Role in Accent Localization for Call Centers appeared first on Krisp.

1. Bruce Temkin

Bruce Temkin is the co-founder of the Customer Experience Professionals Association (CXPA), and recently embarked on a mission to leverage technology and interconnectivity to enhance the human experience. He’s carrying the torch to educate, inspire, and empower leaders to understand how they can better serve the needs of ALL that they serve, including customers, employees, partners, and the communities within which they operate.
Talks about: Experience Management (XM), CX, Human Experience (HX), and disruptive technology

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2. Katie Stabler CCXP

Katie Stabler CCXP is an author, certified CX professional, and speaker who helps organizations design customer-driven cultures and build strategies for improving customer experiences.
Talks about: CX, CX Strategy, Customer-driven cultures

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3. Jay Nathan

Jay Nathan is a 20-year SaaS leader, CX and Growth expert, helping organizations drive success through effective customer-centric strategies.
Talks about: Growth, Customer Experience, SaaS Go-to-market, and Customer Centricity

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4. Annette Franz

Annette Franz is a two-time author, CX enthusiast, and one of Forbes “100 Most Influential Tech Women on Twitter.” With almost 50k followers on social media, Annette shares her passion and knowledge to empower businesses to deliver exceptional customer experiences and build winning organizations that put the customer at the heart of what they do.
Talks about: Customer Understanding, putting the ‘customer’ in Customer Experience, Customer-Centricity, CX and EX

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5. Lisa Stoner

An under-the-radar industry titan, Lisa Stoner heads up Global Support Operations at Meta and has scaled and led support teams of 25K+ across globally across numerous verticals.
Talks about: Enterprise CX, Global Support Operations, cultural transformation, and Customer Loyalty

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6. Cheryl Odee Helm

Cheryl Odee Helm has over 30 years of experience consulting for contact centers and heads up Helm Communications, a consultancy specializing in contact center technologies, operations management, and designing solutions specifically to meet customer expectations.
Talks about: CX, Contact Center Operations, Technology in the Contact Center, and Contact Center Management

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7. Nate Brown

Nate Brown is the Co-Founder of the CX Accelerator community and avid CX transformation accelerator, specializing in empowering employees to deliver on CX’s promise.
Talks about: CX, the Customer Journey, Voice of the Customer (VoC), and Employee Engagement, CX Transformation

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8. James Dodkins

Known as the “Customer Experience Rockstar,” James Dodkins is a CX expert, keynote speaker, and former rockstar who combines humor and practical advice to help organizations create memorable, end-to-end customer journeys and experiences.
Talks about: CX, Corporate Culture, Personalization and Customer Centricity

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9. Dave Michels

Dave Michels is an analyst for TalkingPointz and self-proclaimed Enterprise Communications Protagonist, advocating for better communication and end-user strategies.
Talks about: Enterprise communications, industry analysis, end-user strategy and business communications.

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10. Tom Lewis

Tom Lewis is a global leader in solution architecture and client success, with a passion for driving growth and innovation through a combination of Customer Experience Strategy and AI Enabled Technology.
Talks about: CX trends and transformation, Generative AI, Customer Expectations

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11. Martin Hill-Wilson

Martin Hill-Wilson is a thought leader in the areas of contact centers, CX, and diversity, equity, and inclusion (DEI). He hosts webinars and publishes whitepapers to educate the industry on the latest trends and strategies.
Talks about: CX evolution, Customer Contact Strategy, and DEI

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12. Colin Shaw

Colin Shaw is the CEO of Beyond Philosophy and author of multiple books on CX. His thought leadership provides insights into the psychology behind CX and practical methods for elevating CX to his social media following of nearly 300K CX professionals. Colin’s mission is to enable businesses to create emotionally engaging customer experiences that drive growth and loyalty.
Talks about: CX, Customer Experience & Marketing, Consumer Behavior, Building emotional equity with customers

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13. Dr. Natalie Petouhoff

Dr. Natalie Petouhoff is a best-selling author, speaker, and CX and DEI specialist, bringing a unique blend of expertise to the field to advance the state of CX for organizations and professionals globally. She has over 60K social media followers and for good reason.
Talks about: CX, AI, Employee Experience (EX), and DEI

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14. Susan Hash

Susan Hash is a seasoned customer experience professional, known for her insightful articles and engaging social media presence. With a strong background in contact centers, she shares valuable strategies and industry trends to enhance customer interactions.
Talks about: CX, contact center management strategies, AI & CCaaS

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15. Shep Hyken

Shep Hyken is a renowned customer service and CX expert who has authored several best-selling books. He is a sought-after keynote speaker and consultant, helping organizations create unforgettable customer experiences.
Expertise: Customer Service & CX

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16. Dennis Wakabayashi

Dennis Wakabayashi leads multiple CX communities. He’s a seasoned CX professional who shares his knowledge and experience to help organizations improve their customer experiences.
Talks about: CX, Enterprise Support, Digital Marketing, and Customer Experience Transformation

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17. Mike Aoki

Mike Aoki is a recognized expert in contact center leadership and CX. As a keynote speaker, he shares his knowledge on building effective customer-centric strategies.
Talks about: Contact Center CX, sales training, customer care

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These CX thought leaders harness the Voice of CX (VoCX), delivering valuable insights, strategies, and best practices to help organizations across the globe enhance their customer experience functions. Whether you’re looking for expertise in contact centers, CX technology, or leadership, these voices should be on your radar.

Connect with them on LinkedIn to stay ahead of the latest CX trends and innovations.

Have recommendations of CX thought leaders to follow of your own? We’d love to hear them! Let us know by tagging us on LinkedIn: @KrispHQ

The post Top 17 CX Thought Leaders to Follow in 2024 appeared first on Krisp.

The Distracting Noise Barrier: A Challenge in Contact Centers

Background noise and other voices are an adversary that contact centers have long battled, both for agents in the center and those working at home. Whether it’s the bustling office environment, the cacophony of daily life, or technical issues during remote work, noise can significantly hinder communication. This leads to misunderstandings, repeated conversations, and ultimately, reduced customer satisfaction. The struggle is not only faced by customers trying to reach out but also by agents striving to provide elevated service.

Enter Krisp SDKs: The Game-Changing Solution

Krisp’s Voice Productivity AI software is a groundbreaking solution that is transforming the way contact centers operate by eliminating background noise and voices (other agents, supervisors, even children for agents who work remotely) to exponentially improve voice quality. 

Krisp has emerged as a transformative force by offering an AI-powered voice processing solution that provides crystal-clear digital voice communication experiences. The technology employs advanced machine learning algorithms to filter out background noise, remove other voices and ensure that only the speaker’s voice is transmitted. This means that customers and agents can communicate seamlessly, regardless of their surroundings or physical environment. In addition, Krisp removes the background noise bidirectionally, from the customer to the agent as well, so that agents always clearly understand their customer.

Krisp SDKs integrate into most CCaaS platforms and are available across platforms, including WASM JS, Win, Mac, Linux, Android and iOS and has optimized its package to minimize its footprint and resource utilization while still delivering market-best voice quality performance. Processings real-time communications with no perceived delay added to calls, Krisp SDKs include support for fullband, wideband and narrowband calls. 

Krisp SDKs include:

• Noise Cancellation: microphone (outbound/uplink) stream, robust for noise types and SNR levels.
• Inbound Noise Cancellation: speaker (inbound/downlink): optimized for inbound PTSN/mobile, removes background noise from customer to agent and has intelligence to allow ringtones to pass through to the agent.
• Background Voice Cancellation: removes competing voices around the agent, including other agents and supervisors. There is no need for training or enrolling the agent’s voice. 
• Accent Localization: localizes Indian English accents so that US-based customers hear US-neutral accents. This is done so that there is no perceived delay during the call and agents sound natural in their speech, tones and pitch. Additional geographic accents will be added.

How Krisp’s Voice Productivity AI Works

Krisp’s technology works on a simple yet ingenious principle. It employs two-way voice processing – one deployed in the microphone stream (uplink/outbound) and one in the speaker stream (downlink/inbound). For the agent, the technology uses AI to distinguish between the agent’s voice and background noise and other voices. All noise and competing voices are then canceled out, leaving only the agent’s voice to be transmitted. For the customer’s inbound audio stream, the technology similarly filters out any residual noise, ensuring that the audio received is crisp and clear. 

Krisp SDKs are all integrated on-device with no cloud/server connectivity, processing or storage.

Benefits for Customers

For customers interacting with contact centers, the advantages of Krisp are quantitative and qualitative. First and foremost, the elimination of background noise means that queries and concerns are heard accurately, resulting in quicker issue resolution. This leads to higher customer satisfaction rates and an overall positive perception of the brand’s commitment to quality service. Additionally, improved audio quality reduces the likelihood of miscommunications, misunderstandings, and repetitive conversations. This enhances the overall customer experience and reducing the time required on a call. Krisp contact center customers report on average a 10% reduction in average handle time (AHT), an 8% increase in customer satisfaction scores (CSAT), and a 25% increase in agent satisfaction.

Empowering Contact Center Agents with Voice AI

While the customer experience is paramount, Krisp’s Voice AI technology also greatly benefits contact center agents. Agents are better able to focus on the conversation at hand without struggling to decipher muffled speech or loud distractions. This heightened focus not only boosts their efficiency but also reduces stress levels, leading to improved job satisfaction. With clearer audio, agents can provide more accurate responses, leading to faster call resolutions and increased agent productivity. Agents are able to have clear voice communications independent of their headset type or quality level. In fact, many contact centers using Krisp have reduced their investments and now purchase much lower priced headsets, as Krisp far outperforms and out-delivers even the most expensive headsets.

Bridging the Accent Gap – Accent Localization

Krisp has developed Accent Localization technology to enable clear communications across countries, languages and accents. Starting with India-based agents for North American customers, agent accents are localized to sound similar to North American accents, lessening the friction between consumers and agents equipped to help them solve their problems. Krisp will be adding additional accent coverage in 2024 for most major markets. This highly valuable breakthrough technology will enable highly qualified agents in emerging markets to be able to serve demanding customers comfortably without the risk of unintelligibility or bias from customers due to accent.

Elevating Work from Home

The global shift toward remote work has posed new challenges for contact centers. Agents are now working from a variety of locations, each with its own set of background noises. Krisp has risen to this challenge by offering a powerful solution that ensures remote agents can maintain the same level of professionalism as their office counterparts. Customers never know if any agent is working in a large, loud contact center, or at home with unpredictable background noises.

Integration and Accessibility

One of the remarkable features of Krisp’s Voice AI technology is its ease of integration into existing contact center platforms. This means that contact centers can seamlessly incorporate Krisp’s voice processing capabilities into their operations without disrupting their existing workflows. Krisp integrates with browser-based applications, as well as native applications, both on desktop and mobile. This approach ensures that the power of Krisp is accessible to businesses of all sizes, from enterprise-level platforms to those serving mid-market and SMB.

The Future of Customer-Centric Communication

In a world where customer expectations are continually on the rise, Krisp is leading the way in revolutionizing how contact centers provide clear voice communications. By addressing the perennial challenge of background noise, audio quality and accents, Krisp’s Voice Productivity AI is enhancing customer experiences, boosting agent productivity, and redefining the parameters of efficient communication.

In conclusion, the power of Krisp’s Voice Productivity AI software within contact center platforms is undeniable. It is reshaping the industry by transforming the way customer interactions occur. The technology’s ability to eliminate background noise, block competing voices, localize accents and deliver crystal-clear audio profoundly impacts both customer satisfaction and agent efficiency. As we move forward in this digital age, Krisp plays a pivotal role in shaping the future of customer-centric communication. Contact center platforms embracing this technology will gain a competitive edge, setting new standards in the realm of customer service.

The post Enhancing Contact Center Platforms with the Power of Voice Productivity AI appeared first on Krisp.