NeMo VS vosk-api

I don't test WaveRNN but from the ones that I know the best that is open source is FastPitch. And it's easy to use, here is the tutorial for voice cloning.

Nowadays... bigger repos like https://github.com/NVIDIA/NeMo are all pytorch, lots of work also published by Meta and Microsoft is all torch. I check new work on GitHub all the time and I haven't seen a Tensorflow repo in years except one.

- https://github.com/NVIDIA/NeMo

Can’t you use the NeMo model and just strip the punctuation from the output again if you don’t want it? You can also fine tune the the model with capitalization only if you look at the examples https://github.com/NVIDIA/NeMo/blob/stable/tutorials/nlp/Punctuation_and_Capitalization.ipynb The capitalization and punctuation are annotated separately (U indicates that the word should be upper cased, and O - no capitalization ). The model seems to be a token level classifier not seq to seq so there should also be a way to get just the capitalization part but you would have to look into the model as it’s not shown in the examples.

I think there's been talk to do speaker diarization with whisper-asr-webservice[0] which is also written in python and should be able to make use of goodies such as pyannote-audio, py-webrtcvad, etc.

Whisper is great but at the point we get to kludging various things together it starts to make more sense to use something like Nvidia NeMo[1] which was built with all of this in mind and more

[0] - https://github.com/ahmetoner/whisper-asr-webservice

[1] - https://github.com/NVIDIA/NeMo

[커먼보이스 전자우편](mailto:[email protected]) || Common Voice || Korean Language Homepage || FAQs || Speaking Aloud and Reviewing Recordings || Sentence Collector || NVidia/NeMo

The final security grain was added with speech-to-text anti-spoofing built on QuartzNet from the Nemo framework. This model provides a decent quality user experience and is suitable for real-time scenarios. To measure how close what the person says to what the system expects, requires calculation of the Levenshtein distance between them.

It's coming! CMUSphinx used to have something like this, and there are some [1] solutions [2] on the horizon.

[1]: https://github.com/alphacep/vosk-api/issues/55

[2]: https://github.com/outlines-dev/outlines?tab=readme-ov-file#...

So I don't know if my issue comes from my lack of knowledge of discord.js/voice or VOSK. so I guess the most important thing I need to see is if I am creating a proper stream for the Vosk API to capture the audio. if I can figure out how to capture an audio stream I can probably import that in to vosk and figure out how to use vosk myself. but right now I can't even get close! Thank you in advance...Sorry if this isn't the right place for this

I remember a while ago checking out the issues with Vosk speech recognition (written in C). A handful of it's issues are related to segfaults and null pointers.

first, good initiative! thanks for sharing. i think you gotta be more diligent and careful with the problem statement.

checking the weather in Sofia, Bulgaria requires cloud, current information. it's not "random speech". ESP SR capability issues don't mean that you cannot process it locally.

the comment was on "voice processing" i.e. sending speech to the cloud, not sending a call request to get the weather information.

besides, local intent detection, beyond 400 commands, there are great local STT options, working better than most cloud STTs for "random speech"

https://github.com/alphacep/vosk-api

I did a one-off text to speech tool for someone last year and had pretty good results with VOSK. One upside is that it works offline, although I imagine if you use TTS a lot you'll notice issues I didn't.

You can use vosk-api (https://github.com/alphacep/vosk-api) to listen to your audio, transform it to text, and then post the text to GPT-3, then using the vector sdk, have your responses said by vector.

The set up script wants to download https://github.com/alphacep/vosk-api/releases/download/v0.3.45/vosk-model-en-v0.3.45.zip, but this resource is not found. AFAICT all releases never contained a model file. Remedy: hardcode one model from https://alphacephei.com/vosk/models. I guessed and picked the one with the closest name, vosk-model-en-us-0.22.zip, just so I could continue.