Google Cloud Text-to-Speech VS Kaldi

My friend was a contractor for Hindi TTS at Google https://cloud.google.com/text-to-speech. - Source: Hacker News / 27 days ago

I created an Anki Deck with all of the words from Mini Kore and 300+ Mini Kore sentences from the various documents on minilanguage.com. The deck includes audio for all words and sentences. Audio was generated using the Google Text-to-Speech API. The deck can be found here:. Source: 11 months ago

Under the hood, it is powered by: - Remotion - Google TTS - OpenAI. Source: 11 months ago

Text-to-Speech: Lifelike Speech Synthesis  |  Google Cloud. Source: 12 months ago

Thanks! The synth is Dreamtonics' Synthesizer V, using the SOLARIA voice database from Eclipsed Sounds. What really sold it to me was listening to some beautifully crafted covers from this YouTube channel: https://www.youtube.com/watch?v=KX0lcVr9ugI), which was quite interesting and somewhat pleasant sounding for spoken word vocals, but didn't really have the range or expressiveness I was looking for. - Source: Hacker News / 12 months ago

Yeah, whisper is the closest thing we have, but even it requires more processing power than is present in most of these edge devices in order to feel smooth. I've started a voice interface project on a Raspberry Pi 4, and it takes about 3 seconds to produce a result. That's impressive, but not fast enough for Alexa. From what I gather a Pi 5 can do it in 1.5 seconds, which is closer, so I suspect it's only a... - Source: Hacker News / 3 months ago

You can study CTC in isolation, ignoring all the HMM background. That is how CTC was also originally introduced, by mostly ignoring any of the existing HMM literature. So e.g. Look at the original CTC paper. But I think the distill.pub article (https://distill.pub/2017/ctc/) is also good. For studying HMMs, any speech recognition lecture should cover that. We teach that at RWTH Aachen University but I don't think... - Source: Hacker News / 7 months ago

I also tried Kaldi but the build process was too much for my tiny brain; I've also heard good things about vosk but didn't try that. Source: about 1 year ago

Frameworks as well as toolkits like Kaldi were at first promoted by the research study area, yet nowadays used by both scientists and also market experts, reduced the access obstacle in the advancement of automatic speech recognition systems. Nonetheless, cutting edge methods need big speech data readies to achieve a usable system. Source: over 1 year ago

If you interested in unix-like software design and not yet familiar with kaldi toolkit, you definitely need to check it https://kaldi-asr.org It extended Unix design with archives, control lists and matrices and enabled really flexible unix-like processing. For example, recognition of a dataset looks like this: extract-wav scp:list.scp ark:- | compute-mfcc-feats ark:- ark:- | lattice-decoder-faster final.mdl... - Source: Hacker News / over 1 year ago