faster-whisper
TTS
faster-whisper | TTS | |
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23 | 231 | |
8,899 | 29,420 | |
9.1% | 4.0% | |
8.1 | 9.4 | |
8 days ago | 8 days ago | |
Python | Python | |
MIT License | Mozilla Public License 2.0 |
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faster-whisper
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Creando Subtítulos Automáticos para Vídeos con Python, Faster-Whisper, FFmpeg, Streamlit, Pillow
Faster-whisper (https://github.com/SYSTRAN/faster-whisper)
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Using Groq to Build a Real-Time Language Translation App
For our real-time STT needs, we'll employ a fantastic library called faster-whisper.
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Apple Explores Home Robotics as Potential 'Next Big Thing'
Thermostats: https://www.sinopetech.com/en/products/thermostat/
I haven't tried running a local text-to-speech engine backed by an LLM to control Home Assistant. Maybe someone is working on this already?
TTS: https://github.com/SYSTRAN/faster-whisper
LLM: https://github.com/Mozilla-Ocho/llamafile/releases
LLM: https://huggingface.co/TheBloke/Nous-Hermes-2-Mixtral-8x7B-D...
It would take some tweaking to get the voice commands working correctly.
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Whisper: Nvidia RTX 4090 vs. M1 Pro with MLX
Could someone elaborate how is this accomplished and is there any quality disparity compared to original whisper?
Repos like https://github.com/SYSTRAN/faster-whisper makes immediate sense about why it's faster than the original, but this one, not so much, especially considering it's even much faster.
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Now I Can Just Print That Video
Cool! I had the same project idea recently. You may be interested in this for the step of speech2text: https://github.com/SYSTRAN/faster-whisper
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Distil-Whisper: distilled version of Whisper that is 6 times faster, 49% smaller
That's the implication. If the distil models are same format as original openai models then the Distil models can be converted for faster-whisper use as per the conversion instructions on https://github.com/guillaumekln/faster-whisper/
So then we'll see whether we get the 6x model speedup on top of the stated 4x faster-whisper code speedup.
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AMD May Get Across the CUDA Moat
> While I agree that it's much more effort to get things working on AMD cards than it is with Nvidia, I was a bit surprised to see this comment mention Whisper being an example of "5-10x as performant".
It easily is. See the benchmarks[0] from faster-whisper which uses Ctranslate2. That's 5x faster than OpenAI reference code on a Tesla V100. Needless to say something like a 4080 easily multiplies that.
> https://www.tomshardware.com/news/whisper-audio-transcriptio... is a good example of Nvidia having no excuses being double the price when it comes to Whisper inference, with 7900XTX being directly comparable with 4080, albeit with higher power draw. To be fair it's not using ROCm but Direct3D 11, but for performance/price arguments sake that detail is not relevant.
With all due respect to the author of the article this is "my first entry into ML" territory. They talk about a 5-10 second delay, my project can do sub 1 second times[1] even with ancient GPUs thanks to Ctranslate2. I don't have an RTX 4080 but if you look at the performance stats for the closest thing (RTX 4090) the performance numbers are positively bonkers - completely untouchable for anything ROCm based. Same goes for the other projects I linked, lmdeploy does over 100 tokens/s in a single session with LLama2 13b on my RTX 4090 and almost 600 tokens/s across eight simultaneous sessions.
> EDIT: Also using CTranslate2 as an example is not great as it's actually a good showcase why ROCm is so far behind CUDA: It's all about adapting the tech and getting the popular libraries to support it. Things usually get implemented in CUDA first and then would need additional effort to add ROCm support that projects with low amount of (possibly hobbyist) maintainers might not have available. There's even an issue in CTranslate2 where they clearly state no-one is working to get ROCm supported in the library. ( https://github.com/OpenNMT/CTranslate2/issues/1072#issuecomm... )
I don't understand what you're saying here. It (along with the other projects I linked) are fantastic examples of just how far behind the ROCm ecosystem is. ROCm isn't even on the radar for most of them as your linked issue highlights.
Things always get implemented in CUDA first (ten years in this space and I've never seen ROCm first) and ROCm users either wait months (minimum) for sub-par performance or never get it at all.
[0] - https://github.com/guillaumekln/faster-whisper#benchmark
[1] - https://heywillow.io/components/willow-inference-server/#ben...
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Open Source Libraries
guillaumekln/faster-whisper
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Whisper Turbo: transcribe 20x faster than realtime using Rust and WebGPU
Neat to see a new implementation, although I'll note that for those looking for a drop-in replacement for the whisper library, I believe that both faster-whisper https://github.com/guillaumekln/faster-whisper and https://github.com/m-bain/whisperX are easier (PyTorch-based, doesn't require a web browser), and a lot faster (WhisperX is up to 70X realtime).
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Whisper.api: An open source, self-hosted speech-to-text with fast transcription
One caveat here is that whisper.cpp does not offer any CUDA support at all, acceleration is only available for Apple Silicon.
If you have Nvidia hardware the ctranslate2 based faster-whisper is very very fast: https://github.com/guillaumekln/faster-whisper
TTS
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OpenAI deems its voice cloning tool too risky for general release
lol this marketing technique is getting very old. https://github.com/coqui-ai/TTS is already amazing and open source.
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What things are happening in ML that we can't hear oer the din of LLMs?
Not sure how relevant this is but note that Coqui TTS (the realistic TTS) has already shut down
https://coqui.ai
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Base TTS (Amazon): The largest text-to-speech model to-date
I've used coqui.ai's TTS models[0] and library[1] to great success. I was able to get cloned voice to be rendered in about 80% of the audio clip length, and I believe you can also stream the response. Do note the model license for XTTS, it is one they wrote themselves that has some restrictions.
[0] https://huggingface.co/coqui/XTTS-v2
[1] https://github.com/coqui-ai/TTS
- FLaNK Stack Weekly 12 February 2024
- Coqui Is Shutting Down
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Coqui.ai Is Shutting Down
My only exposure to Coqui was their text to speech software. If I remember correctly the website was a commercialized service with TTS and probably some other related things. I hope the software work continues in the open.
https://github.com/coqui-ai/TTS
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Hello guys, any selfhosted alternative to eleven labs?
Coqui.ai TTS (https://github.com/coqui-ai/TTS)
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Demo of Anagnorisis - completely local recommendation system powered by Llama 2. Radio mode. Work in progress.
"tts_models/multilingual/multi-dataset/xtts_v2" model from https://github.com/coqui-ai/TTS. It gives pretty good results and works with references, so it's pretty easy to change the voice. By the way the source code of the project is open: https://github.com/volotat/Anagnorisis but be ready, the code is pretty raw for now.
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XTTS voice cloning with only a seconds of audio
A recent update to their GitHub also has a no-code gradio ui to facilitate fine-tuning and inferencing locally. https://github.com/coqui-ai/TTS/releases/tag/v0.21.3
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At a loss trying to get coqui_tts extension to load
No API token found for 🐸Coqui Studio voices - https://coqui.ai
What are some alternatives?
whisper.cpp - Port of OpenAI's Whisper model in C/C++
tortoise-tts - A multi-voice TTS system trained with an emphasis on quality
whisperX - WhisperX: Automatic Speech Recognition with Word-level Timestamps (& Diarization)
Real-Time-Voice-Cloning - Clone a voice in 5 seconds to generate arbitrary speech in real-time
stable-ts - Transcription, forced alignment, and audio indexing with OpenAI's Whisper
silero-models - Silero Models: pre-trained speech-to-text, text-to-speech and text-enhancement models made embarrassingly simple
whisper-diarization - Automatic Speech Recognition with Speaker Diarization based on OpenAI Whisper
vosk-api - Offline speech recognition API for Android, iOS, Raspberry Pi and servers with Python, Java, C# and Node
ROCm - AMD ROCm™ Software - GitHub Home [Moved to: https://github.com/ROCm/ROCm]
text-generation-webui - A Gradio web UI for Large Language Models. Supports transformers, GPTQ, AWQ, EXL2, llama.cpp (GGUF), Llama models.
whisper-realtime - Whisper runs in realtime on a laptop GPU (8GB)
piper - A fast, local neural text to speech system