generate-subtitles VS NeMo

They generate .SRT files, and you can view their repository there.

I use this script to generate text layers based on the srt file I got by using this website.

I do a lot of transcriptions in my job, most of the websites suggested in other comments requiere an account and payments, https://freesubtitles.ai is free and you don’t need an account, you could pay to get premium services but it’s not mandatory

The translation part most likely won't work out all that well, but for JAV (˵ ͡° ͜ʖ ͡°˵) I've used https://freesubtitles.ai/ to get the original audio in subtitle format and then used DeepL to get it translated to English. DeepL doesn't support Hebrew though, but I also tried the AWS' whateveritwascalled and it was okay-ish, maybe check out if they support it.

You can download the audio and then get a transcript/subtitles with freesubtitles.ai

Hey guys I am the developer of https://freesubtitles.ai, I am really satisfied with the quality of the transcriptions now and wanted to share it around a bit, you can use it to transcribe content from over 100 different languages and automatically translate it to over 100 different languages for free. I have been using it to watch movies in foreign languages and it works pretty well, hope it can serve as an alternative to trying to find already made subtitles online, cheers!

I just finished my free transcription app and wanted to share it around a bit. You can use it to transcribe content in over 100 languages and have it translated to over 100 languages all for free. Hope this can be useful in some way, cheers! https://freesubtitles.ai

Whisper AI is a game changer as far as transcribing lyrics don’t know if genius is up on it /u/grinchnight14. https://freesubtitles.ai/ for free without needing to do any coding

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

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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.