July 14, 2021

Exploring The SpeechBrain Toolkit For Speech Processing

37 minutes

Summary

With the rising availability of computation in everyday devices, there has been a corresponding increase in the appetite for voice as the primary interface. To accomodate this desire it is necessary for us to have high quality libraries for being able to process and generate audio data that can make sense of human speech. To facilitate research and industry applications for speech data Mirco Ravanelli and Peter Plantinga are building SpeechBrain. In this episode they explain how it works under the hood, the projects that they are using it for, and how you can get started with it today.

Announcements

Hello and welcome to Podcast.__init__, the podcast about Python’s role in data and science.

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Your host as usual is Tobias Macey and today I’m interviewing Mirco Ravanelli and Peter Plantinga about SpeechBrain, an open-source and all-in-one speech toolkit powered by PyTorch

Interview

Introductions

How did you get introduced to Python?

Can you describe what SpeechBrain is and the story behind it?

What are the goals and target use cases of the SpeechBrain project?

What are some of the ways that processing audio with a focus on speech differs from more general audio processing?

What are some of the other libraries/frameworks/services that are available to work with speech data and what are the unique capabilities that SpeechBrain offers?

How is SpeechBrain implemented?

What was your decision process for determining which framework to build on top of?

What are some of the original ideas and assumptions that you had for SpeechBrain which have been changed or invalidated as you worked through implementing it?

Can you talk through the workflow of using SpeechBrain?

What would be involved in developing a system to automate transcription with speaker recognition and diarization?

In the documentation it mentions that SpeechBrain is built to be used for research purposes. What are some of the kinds of research that it is being used for?

What are some of the features or capabilities of SpeechBrain which might be non-obvious that you would like to highlight?

What are the most interesting, innovative, or unexpected ways that you have seen SpeechBrain used?

What are the most interesting, unexpected, or challenging lessons that you have learned while working on SpeechBrain?

When is SpeechBrain the wrong choice?

What do you have planned for the future of SpeechBrain?

Keep In Touch

Mirco

mravanelli on GitHub

@mirco_ravanelli on Twitter

Peter

pplantinga on GitHub

@ComPeterScience on Twitter

Website

Picks

Tobias

x.ai

Closing Announcements

Thank you for listening! Don’t forget to check out our other show, the Data Engineering Podcast for the latest on modern data management.

Visit the site to subscribe to the show, sign up for the mailing list, and read the show notes.

If you’ve learned something or tried out a project from the show then tell us about it! Email [email protected]) with your story.

To help other people find the show please leave a review on iTunes and tell your friends and co-workers

Join the community in the new Zulip chat workspace at pythonpodcast.com/chat

Links

SpeechBrain

Mila

Speech Processing

Speech Enhancement

NumPy

SciPy

Theano

PyTorch

Podcast Episode

Speech Recognition

NeMo

ESPNet

Sequence to Sequence (Seq2Seq)

HyperParameters

TorchAudio

PyTorch Lightning

Keras

HuggingFace

Generative Adversarial Network

Snorkel

Data Engineering Podcast Episode

The intro and outro music is from Requiem for a Fish The Freak Fandango Orchestra / CC BY-SA

...more

View all episodes

By Tobias Macey

4.4

100100 ratings

July 14, 2021

Exploring The SpeechBrain Toolkit For Speech Processing

37 minutes

Summary

Announcements

Hello and welcome to Podcast.__init__, the podcast about Python’s role in data and science.

Your host as usual is Tobias Macey and today I’m interviewing Mirco Ravanelli and Peter Plantinga about SpeechBrain, an open-source and all-in-one speech toolkit powered by PyTorch

Interview

Introductions

How did you get introduced to Python?

Can you describe what SpeechBrain is and the story behind it?

What are the goals and target use cases of the SpeechBrain project?

What are some of the ways that processing audio with a focus on speech differs from more general audio processing?

What are some of the other libraries/frameworks/services that are available to work with speech data and what are the unique capabilities that SpeechBrain offers?

How is SpeechBrain implemented?

What was your decision process for determining which framework to build on top of?

What are some of the original ideas and assumptions that you had for SpeechBrain which have been changed or invalidated as you worked through implementing it?

Can you talk through the workflow of using SpeechBrain?

What would be involved in developing a system to automate transcription with speaker recognition and diarization?

In the documentation it mentions that SpeechBrain is built to be used for research purposes. What are some of the kinds of research that it is being used for?

What are some of the features or capabilities of SpeechBrain which might be non-obvious that you would like to highlight?

What are the most interesting, innovative, or unexpected ways that you have seen SpeechBrain used?

What are the most interesting, unexpected, or challenging lessons that you have learned while working on SpeechBrain?

When is SpeechBrain the wrong choice?

What do you have planned for the future of SpeechBrain?

Keep In Touch

Mirco

mravanelli on GitHub

@mirco_ravanelli on Twitter

Peter

pplantinga on GitHub

@ComPeterScience on Twitter

Website

Picks

Tobias

x.ai

Closing Announcements

Thank you for listening! Don’t forget to check out our other show, the Data Engineering Podcast for the latest on modern data management.

Visit the site to subscribe to the show, sign up for the mailing list, and read the show notes.

If you’ve learned something or tried out a project from the show then tell us about it! Email [email protected]) with your story.

To help other people find the show please leave a review on iTunes and tell your friends and co-workers

Join the community in the new Zulip chat workspace at pythonpodcast.com/chat

Links

SpeechBrain

Mila

Speech Processing

Speech Enhancement

NumPy

SciPy

Theano

PyTorch

Podcast Episode

Speech Recognition

NeMo

ESPNet

Sequence to Sequence (Seq2Seq)

HyperParameters

TorchAudio

PyTorch Lightning

Keras

HuggingFace

Generative Adversarial Network

Snorkel

Data Engineering Podcast Episode

The intro and outro music is from Requiem for a Fish The Freak Fandango Orchestra / CC BY-SA

...more

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Exploring The SpeechBrain Toolkit For Speech Processing

Exploring The SpeechBrain Toolkit For Speech Processing

More shows like The Python Podcast.init

TED Talks Daily

6 Minute English

The Changelog: Software Development, Open Source

Data Skeptic

Talk Python To Me

Software Engineering Daily

The TWIML AI Podcast (formerly This Week in Machine Learning & Artificial Intelligence)

Super Data Science: ML & AI Podcast with Jon Krohn

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Syntax - Tasty Web Development Treats

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Practical AI

The Real Python Podcast

Last Week in AI

Latent Space: The AI Engineer Podcast