Democratizing ML for speech

You might know about MLPerf, a benchmark from MLCommons that measures how fast systems can train models to a target quality metric. However, MLCommons is working on so much more! David Kanter joins us in this episode to discuss two new speech datasets that are democratizing machine learning for speech via data scale and language/speaker diversity.

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Featuring:

• David Kanter – GitHub, X
• Chris Benson – Website, GitHub, LinkedIn, X
• Daniel Whitenack – Website, GitHub, X

Show Notes:

• Press Release about MLCommons datasets: MLCommons™ Association Unveils Open Datasets and Tools to Drive Democratization of Machine Learning
• NeurIPS Papers: 
  • People’s Speech Dataset
  • Multilingual Spoken Words Corpus (MSWC)
• Gradient article: New Datasets to Democratize Speech Recognition Technology
• Blog posts for more insight: 
  • People’s Speech
  • Multilingual Spoken Words Corpus (MSWC)
• Downloads: 
  • People’s Speech
  • Multilingual Spoken Words Corpus

Something missing or broken? PRs welcome!

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Creators & Guests

Host

Chris Benson

Host

Daniel Whitenack

Guest

David Kanter

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