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Why on earth are they using mp3 for the dataset? Its absolutely ancient and probably the worst choice possible. Opus is widely used for voice because it gets fl
by Polylactic_acid 6y ago
Why on earth are they using mp3 for the dataset? Its absolutely ancient and probably the worst choice possible. Opus is widely used for voice because it gets flawless results at minuscule bitrates. And don't tell me its because users find mp3 simpler because if you are doing machine learning I expect you know how to use an audio file.
- lunixbochs 6y agoProbably because they're uploading (and playing back) from a webpage and Web Audio is weird and inconsistent, so sticking to a builtin codec is probably more reliable. As someone who trains on their data, it seems usable anyway. Training on 1000 hours of Common Voice makes my model better in very clear ways. https://caniuse.com/#search=mp3 https://caniuse.com/#search=mp3 https://caniuse.com/#search=opus https://caniuse.com/#search=opus I got flac working for speech.talonvoice.com with an asm codec so they could do whatever in theory, but I do get some audio artifacts sometimes.
- est31 6y agoYeah especially compatibility with Apple browsers was very important for them. I'd added functionality to normalize audio for verification but they removed it multiple times because it didn't work on Safari for various reasons. I ended up building an extension for Firefox that normalizes the audio on the website if installed: https://github.com/est31/vmo-audio-normalizer https://github.com/est31/vmo-audio-normalizer https://addons.mozilla.org/de/firefox/addon/vmo-audio-normalizer/ https://addons.mozilla.org/de/firefox/addon/vmo-audio-normal... In general I don't think normalization should happen at the backend. It's useful for training data to have multiple loudness levels, so that the network can understand them all.