faster-whisper

Faster Whisper transcription with CTranslate2 (by SYSTRAN)

Faster-whisper Alternatives

Similar projects and alternatives to faster-whisper

NOTE: The number of mentions on this list indicates mentions on common posts plus user suggested alternatives. Hence, a higher number means a better faster-whisper alternative or higher similarity.

faster-whisper reviews and mentions

Posts with mentions or reviews of faster-whisper. We have used some of these posts to build our list of alternatives and similar projects. The last one was on 2024-04-05.
  • Using Groq to Build a Real-Time Language Translation App
    3 projects | dev.to | 5 Apr 2024
    For our real-time STT needs, we'll employ a fantastic library called faster-whisper.
  • Apple Explores Home Robotics as Potential 'Next Big Thing'
    3 projects | news.ycombinator.com | 4 Apr 2024
    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.

  • Whisper: Nvidia RTX 4090 vs. M1 Pro with MLX
    10 projects | news.ycombinator.com | 13 Dec 2023
    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.

  • Now I Can Just Print That Video
    5 projects | news.ycombinator.com | 4 Dec 2023
    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
  • Distil-Whisper: distilled version of Whisper that is 6 times faster, 49% smaller
    14 projects | news.ycombinator.com | 31 Oct 2023
    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.

  • AMD May Get Across the CUDA Moat
    8 projects | news.ycombinator.com | 6 Oct 2023
    > 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...

  • Open Source Libraries
    25 projects | /r/AudioAI | 2 Oct 2023
    guillaumekln/faster-whisper
  • Whisper Turbo: transcribe 20x faster than realtime using Rust and WebGPU
    3 projects | news.ycombinator.com | 12 Sep 2023
    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).
  • Whisper.api: An open source, self-hosted speech-to-text with fast transcription
    5 projects | news.ycombinator.com | 22 Aug 2023
    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

  • LeMUR: LLMs for Audio and Speech
    1 project | news.ycombinator.com | 27 Jul 2023
    Comparison by competitor but it’s believable IMO. Basically about the same performance as whisper:

    - https://deepgram.com/learn/nova-speech-to-text-whisper-api

    Not surprising though as at this level all these options are starting to be leveled by inconsistencies in manual groundtruth. Conformed alone also isn’t the most powerful architecture out there for speech. This is also slower than, say running a large k2 zipformer via onnx on cpu.

    Also if you have a small shop at this point you can do all of this yourself with whisper large v2 on a single 16gb gpu via some tweaking of https://github.com/guillaumekln/faster-whisper and an odd LLM.

    Interesting stuff but I think margins in this space are getting ready to simply vanish.

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