EPISODE · Jan 19, 2022 · 44 MIN
Democratizing ML for speech (Practical AI #164)
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.
Embed this episode
NOW PLAYING
Democratizing ML for speech (Practical AI #164)
0:00
44:50
1×
No transcript for this episode yet
Similar Episodes
No similar episodes found.
Similar Podcasts
No similar podcasts found.
Frequently Asked Questions
How long is this episode of Changelog Master Feed?
This episode is 44 minutes long.
When was this Changelog Master Feed episode published?
This episode was published on January 19, 2022.
Is there a transcript available for this episode?
Yes, a full transcript is available for this episode. You can read the complete transcript on the episode page.
Can I download this Changelog Master Feed episode?
Yes. Use the download control on the episode player to save the publisher-provided media file.
URL copied to clipboard!