Retrieval-based-Voice-Conversion-WebUI VS whisper.cpp

RVC does live voice changing with a little latency: https://github.com/RVC-Project/Retrieval-based-Voice-Convers...

The product isn't exactly spectacular, but most of the works seems to have bene done. Just needs someone to go over the UI and make it less unstable, really.

Retrieval-based-Voice-Conversion-WebUI. Nearly destroyed a hard drive in the process of getting the fucking thing to train on Vito's voice but it came together eventually.

Yeah, Man all the AI tools are fun RVC is fun to play with as well.

Would it be possible to reverse a AI generated voice if they spoke themselves[0] instead of using TTS[1]?

Since the AI voice is trained shouldn't a reversing AI also be able to seperate the trained data?

[0] https://github.com/RVC-Project/Retrieval-based-Voice-Conversion-WebUI

Well fortunately most people I see making AI cover they use open source tools to do that (https://github.com/RVC-Project/Retrieval-based-Voice-Convers...)

RVC-Project/Retrieval-based-Voice-Conversion-WebUI: Singing Voice Conversion

At least that's what https://github.com/RVC-Project/Retrieval-based-Voice-Convers... links to

Realtime Voice Conversion Software using RVC : w-okada/voice-changer

I don't know how to use it yet, but the program is here. https://github.com/RVC-Project/Retrieval-based-Voice-Conversion-WebUI/blob/main/docs/README.en.md

whisper.cpp [1] has a karaoke example that uses ffmpeg's drawtext filter to display rudimentary karaoke-like captions. It also supports diarisation. Perhaps it could be a starting point to create a better script that does what you need.

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1: https://github.com/ggerganov/whisper.cpp/blob/master/README....

The ggml library is one of the first library for local LLM interference. It’s a pure C library that converts models to run on several devices, including desktops, laptops, and even mobile device - and therefore, it can also be considered as a tinkering tool, trying new optimizations, that will then be incorporated into other downstream projects. This tool is at the heart of several other projects, powering LLM interference on desktop or even mobile phones. Subprojects for running specific LLMs or LLM families exists, such as whisper.cpp.

I'm not sure if it is _fully_ openai compatible, but whispercpp has a server bundled that says it is "OAI-like": https://github.com/ggerganov/whisper.cpp/tree/master/example...

I don't have any direct experience with it... I've only played around with whisper locally, using scripts.

unless i'm misunderstanding `whisper.cpp` seems to support streaming & the repository includes a native example[0] and a WASM example[1] with a demo site[2].

[0]: https://github.com/ggerganov/whisper.cpp/tree/master/example...

Usage 1: Good to transcribe audio. An example use case could be to summarize YouTube videos or long courses. Usage 2: You talk with voice to your AI that responds with text (later with audio too). - https://github.com/ggerganov/whisper.cpp

🗣️🎙️ whisper.cpp (offline speech-to-text transcription, models trained by OpenAI, CLI based, browser based)

Has anyone played around with Whisper C++ for swift? I'm hitting a snag even on the demo. I've downloaded the github repo and everything matches up with this video [ https://youtu.be/b10OHCDHDQ4 ] but when he hits the transcribe button, it actually prints out the captioning. When I do it, it skips that part and just says "Done...". But it, does everything else - plays the audio, says it's transcribing.. just doesn't show me the transcription: and it's not in the debug window either. But the demo isn't throwing any errors, and I haven't messed with the code really so this is their example. https://github.com/ggerganov/whisper.cpp