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#255 The Rise of Voice Productivity with Krisp CEO Davit Baghdasaryan

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Manage episode 491106524 series 2975363
Content provided by Slator. All podcast content including episodes, graphics, and podcast descriptions are uploaded and provided directly by Slator or their podcast platform partner. If you believe someone is using your copyrighted work without your permission, you can follow the process outlined here https://staging.podcastplayer.com/legal.

Davit Baghdasaryan, Co-Founder & CEO of Krisp, joins SlatorPod to talk about the platform’s journey from a noise cancellation tool to a comprehensive voice productivity solution.

Originally built to eliminate background noise during calls, Krisp has expanded into real-time accent conversion, speech translation, agent assistance, and note-taking — technologies being rapidly adopted in enterprise environments.

The company’s accent conversion is now deployed by tens of thousands of call center agents, significantly improving metrics like customer satisfaction and call handling time.

Davit details Krisp’s live AI speech translation feature which uses a multi-step pipeline of speech-to-text, text translation, and text-to-speech. The majority of use cases are in high-resource language pairs such as English, Spanish, French, and German, although Davit recognizes the importance of expanding to lower-resource languages.

He shares how Krisp is also seeing increased demand in human-to-AI voice communication. AI voice agents are highly sensitive to background noise, which disrupts turn-taking and response accuracy. Krisp’s noise isolation tech plays a foundational role in enabling smoother voice AI interactions, with billions of minutes processed monthly by major AI labs and startups.

The CEO discusses LLMs' impact, noting how they enable advanced features like note-taking, call summaries, and real-time agent guidance. He sees Krisp as a platform combining proprietary technologies with third-party AI to serve both B2B and B2C markets.

Davit advises startups to explore the vast and still underdeveloped voice AI landscape, noting the current era is ripe for innovation due to AI advancements. He highlights Krisp’s roadmap priorities: expanding accent packs, refining voice translation, and building more AI Agent Assist tools focused on voice workflows.

  continue reading

Chapters

1. Intro (00:00:00)

2. Professional Background and Founding Krisp (00:01:15)

3. Beginning with a Noice Cancellation Tool (00:03:43)

4. A Leader in Voice Productivity (00:06:41)

5. Integrations and Product Offerings (00:08:42)

6. Impact of LLMs (00:12:40)

7. Deploying Accent Conversion (00:15:10)

8. Difference Between Accent Localization and Language Conversion (00:19:09)

9. Language Combinations (00:20:46)

10. Competitive Landscape in Speech Translation (00:24:03)

11. Metrics for Success in Call Centers (00:26:26)

12. Strategies for Growth (00:28:09)

13. Evolution of Products from Noise Cancellation to Call Center Solutions (00:30:01)

14. Startup Environment (00:32:43)

15. Roadmap for Speech and Voice Translation (00:34:57)

255 episodes

Artwork
iconShare
 
Manage episode 491106524 series 2975363
Content provided by Slator. All podcast content including episodes, graphics, and podcast descriptions are uploaded and provided directly by Slator or their podcast platform partner. If you believe someone is using your copyrighted work without your permission, you can follow the process outlined here https://staging.podcastplayer.com/legal.

Davit Baghdasaryan, Co-Founder & CEO of Krisp, joins SlatorPod to talk about the platform’s journey from a noise cancellation tool to a comprehensive voice productivity solution.

Originally built to eliminate background noise during calls, Krisp has expanded into real-time accent conversion, speech translation, agent assistance, and note-taking — technologies being rapidly adopted in enterprise environments.

The company’s accent conversion is now deployed by tens of thousands of call center agents, significantly improving metrics like customer satisfaction and call handling time.

Davit details Krisp’s live AI speech translation feature which uses a multi-step pipeline of speech-to-text, text translation, and text-to-speech. The majority of use cases are in high-resource language pairs such as English, Spanish, French, and German, although Davit recognizes the importance of expanding to lower-resource languages.

He shares how Krisp is also seeing increased demand in human-to-AI voice communication. AI voice agents are highly sensitive to background noise, which disrupts turn-taking and response accuracy. Krisp’s noise isolation tech plays a foundational role in enabling smoother voice AI interactions, with billions of minutes processed monthly by major AI labs and startups.

The CEO discusses LLMs' impact, noting how they enable advanced features like note-taking, call summaries, and real-time agent guidance. He sees Krisp as a platform combining proprietary technologies with third-party AI to serve both B2B and B2C markets.

Davit advises startups to explore the vast and still underdeveloped voice AI landscape, noting the current era is ripe for innovation due to AI advancements. He highlights Krisp’s roadmap priorities: expanding accent packs, refining voice translation, and building more AI Agent Assist tools focused on voice workflows.

  continue reading

Chapters

1. Intro (00:00:00)

2. Professional Background and Founding Krisp (00:01:15)

3. Beginning with a Noice Cancellation Tool (00:03:43)

4. A Leader in Voice Productivity (00:06:41)

5. Integrations and Product Offerings (00:08:42)

6. Impact of LLMs (00:12:40)

7. Deploying Accent Conversion (00:15:10)

8. Difference Between Accent Localization and Language Conversion (00:19:09)

9. Language Combinations (00:20:46)

10. Competitive Landscape in Speech Translation (00:24:03)

11. Metrics for Success in Call Centers (00:26:26)

12. Strategies for Growth (00:28:09)

13. Evolution of Products from Noise Cancellation to Call Center Solutions (00:30:01)

14. Startup Environment (00:32:43)

15. Roadmap for Speech and Voice Translation (00:34:57)

255 episodes

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