Agreed. I distinctly remember it becoming worth using in 2015, and was using that as my reference point. Since then it’s probably improved, but it’s been gradual enough I haven’t noticed as it happens. Everything Alex cites came after 2015, so I wasn’t counting that as “had major discontinuities in line with the research discontinuities”.
However I think foreign language translation has experienced such a discontinuity, and it’s y of comparable magnitude to the wishlist.
Prior to DL text-to-speech used hidden markov models. Those were replaced with LSTMs relatively early in the DL-revolution (random 2014 paper). In 2015 there were likely still many HHM-based models around, but apparently at least Google already used DL-based text-to-speech.
Agreed. I distinctly remember it becoming worth using in 2015, and was using that as my reference point. Since then it’s probably improved, but it’s been gradual enough I haven’t noticed as it happens. Everything Alex cites came after 2015, so I wasn’t counting that as “had major discontinuities in line with the research discontinuities”.
However I think foreign language translation has experienced such a discontinuity, and it’s y of comparable magnitude to the wishlist.
Was circa 2015 speech-to-text using deep learning? If not, how did it work?
Prior to DL text-to-speech used hidden markov models. Those were replaced with LSTMs relatively early in the DL-revolution (random 2014 paper). In 2015 there were likely still many HHM-based models around, but apparently at least Google already used DL-based text-to-speech.