Kaldi VS Kaldi ASR

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 / 4 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

Additionally, C++ may be used for extremely high levels of optimization even for cloud-based ML. Dlib and Kaldi are C++ libraries used as dependencies in Python codebases for computer vision and audio processing, for example. So if your application requires you to customize any functions similar to those libraries, then you'll need C++ knowhow. Source: over 1 year ago

I'm not how sure it stacks with recent state of art, but Kaldi toolkit (https://github.com/kaldi-asr/kaldi) used to be popular for building all kinds of practical integrations and experiments for speech recognition. Source: about 2 years ago

Vosk-api isn't an SST engine itself, it is built using the Kaldi speech recognition toolkit (https://github.com/kaldi-asr/kaldi) and nicely implements and packages an API for Kaldi chain/LF-MMI models. - Source: Hacker News / over 2 years ago