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072: Introducing Owl: PolyAI's in-house speech recognition model

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Content provided by Team PolyAI. All podcast content including episodes, graphics, and podcast descriptions are uploaded and provided directly by Team PolyAI 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://ppacc.player.fm/legal.

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Guest host Meghan Berton and VP of Engineering Razvan Kusztos cover the release of PolyAI's Owl ASR model, while dishing goss on the intricacies of developing high-performing speech recognition models. They discuss the significance of in-house SLU tech, the challenges of ensuring accuracy across different accents and environments, and the benefits of using synthetic data. The conversation also covers the cultural nuances in text to speech models and how Poly AI leverages partnerships with companies like NVIDIA for enhanced model performance.

Follow PolyAI on LinkedIn
Watch this and other episodes of the Deep Learning pod on YouTube

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72 episodes

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iconShare
 
Manage episode 485667953 series 3533896
Content provided by Team PolyAI. All podcast content including episodes, graphics, and podcast descriptions are uploaded and provided directly by Team PolyAI 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://ppacc.player.fm/legal.

Send us a text

Guest host Meghan Berton and VP of Engineering Razvan Kusztos cover the release of PolyAI's Owl ASR model, while dishing goss on the intricacies of developing high-performing speech recognition models. They discuss the significance of in-house SLU tech, the challenges of ensuring accuracy across different accents and environments, and the benefits of using synthetic data. The conversation also covers the cultural nuances in text to speech models and how Poly AI leverages partnerships with companies like NVIDIA for enhanced model performance.

Follow PolyAI on LinkedIn
Watch this and other episodes of the Deep Learning pod on YouTube

  continue reading

72 episodes

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