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@HassanSb_ Check out what we've built! at16k.com
This is part of our roadmap at at16k.com. Shift the focus back to user privacy with on-device recognition APIs.
Fast, local, low-power machine learning models that do speech transcriptions on mobile phones mess up a lot of existing business models but unlocks all sorts of value for the world.
@jamescham We are trying to get there with at16k.com. Do take a look!
@SlangLabs @mozilla Absolutely. We're releasing streaming APIs in the next version! Stay tuned :)
Market Research Trends: Voice And Speech Recognition Market Growth Rate, D... market24trends.blogspot.com/2020/01/voice-…
We have open-sourced wav2letter@anywhere, an inference framework for online speech recognition that delivers state-of-the-art performance. ai.facebook.com/blog/online-sp…
Facebook AI has released Libri-light, the largest open source data set for speech recognition to date. This new benchmark helps researchers pretrain acoustic models to understand speech, with few to no labeled examples. ai.facebook.com/blog/a-new-ope…
#speech #MachineLearning #speechtotext #speechrecognition
Just released the first version of at16k - at16k.com Open source, production quality models for speech to text. Trained with @TensorFlow and @googlecloud TPUs. Gotta say that the TPUs are really really fast. 7 days of training down to 12 hours!
strauseandrew @StrauseAndrew
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