Whistle: Speech to Text in 16.9 MB

(cactuscompute.com)

94 points | by gmays 1 hour ago

14 comments

  • INTPenis 37 minutes ago
    I don't think the challenge with speech to text was size of the binary. In my experience the challenge is understanding my 84 year old Croatian father with a sagging mouth after a stroke, when he's trying to write his autobiography.

    I just setup Windows speech to text for him last week and it's great to see how he can write an entire page in 10 minutes, it would take him days using the keyboard.

    But every single sound he makes with his mouth ends up on the page too.

    • ComputerGuru 31 minutes ago
      Sorry about your father. He needs a dictation model, not a general purpose speech-to-text model. They ignore umms and ahhs, change things like “an elephant, no a monkey, went up the tree” to “a monkey went up the tree,” support saying punctuation aloud sometimes, etc.

      Gemini team just released Gemini 3.5 Transcribe that’s supposed to be good at this; it’s available via api: https://blog.google/innovation-and-ai/models-and-research/ge...

      • cgbur 9 minutes ago
        For essentially infinite and fast dictation I use https://github.com/cjpais/Handy on Parakeet streaming (cohere is far better, but slower and has a token output limit so you cant ramble for many minutes). And then just do a cleanup pass with a cheap LLM, it will in my experience, do far better than trying to voice control to go edit a sentence or change words. I just weave instructions into my writing. I understand this requires technical know-how, but for those with it, this is the best solution I have found to long form writing without my hands.
    • boplicity 14 minutes ago
      There are many different challenges, each requiring their own solution. I, for one, really miss the old Google Assistant on my Android phone. It would very reliably play most songs that I wanted to hear on Spotify. Gemini fails at this almost every time, and is significantly slower. It's actually a difficult problem, as the songs people want to hear are regularly being released, are often associated with uncommon names, or have words in unusual orders, so normal LLM style tools just don't cut it.
    • yymir 7 minutes ago
      i mean for something this small, it can be fit into a l3 cache on a cpu and be essentially always on various purposes
    • testycool 13 minutes ago
      Unrelated: I love your username.
  • joewhale 34 minutes ago
    I initially read this as whistle to text, which would be way cooler.
  • kamranjon 18 minutes ago
    Sooo I haven't really been super impressed with the needle models before, but this is very impressive. It transcribed multiple sentences I gave it with complex timing and words and in such a small footprint, I'm super impressed. Excited to see what types of things can be built with something like this, the performance seems very good.
  • andy_ppp 42 minutes ago
    Wow certainly in English this is incredibly accurate I tried to break it and it understood me perfectly!

    I know it's slightly off topic but surely it must be easy by now to train a spell checker that doesn't annoy the crap out of everyone using it (looking at you here Apple)!

  • mo2art 9 minutes ago
    RuntimeError: audio limit is 30 s
    • jjice 1 minute ago
      Did you record over 30 seconds?
  • armcat 26 minutes ago
    Those are insane benchmarks at this size. Well done!
  • mrkn1 25 minutes ago
    love seeing more sub-20MB, CPU-first models. if anyone wants a CLI built on the same ethos (no GPU, no cloud), been using yapsnap streaming Zipformer ASR, plus diarization and timestamps all on CPU! It supports 10 languages.
  • tecleandor 42 minutes ago
    Spanish is not good (seems to write non existing words and/or with terrible typos...) but English seem to work good even with my (Spanish) accent...
    • kaoD 41 minutes ago
      Spanish from where? Here (Castilian Spanish) it seemed to work fine.
      • tecleandor 12 minutes ago
        Madrid. But it will only work properly if I'm clearly dictating with a very regular rhythm (ViaVoice dictation, if anyone remembers...). If I use a more natural/conversational rhythm (no slang, no abbreviations...) it easily confuses words.
      • chilicuil 14 minutes ago
        Mexican and venezuelan aren't detected correctly
  • aidotguru 17 minutes ago
    eager to see if working in android phones
    • rpdillon 14 minutes ago
      FUTO keyboard (open-source, free) runs entirely on-device and has extremely good STT accurary, especially with the 70M parameter model. I've used it for years now and love it.

      https://futo.tech/

  • agilek 4 minutes ago
    Can we have more languages?
  • saturn8601 38 minutes ago
    Initial tests make this feel just like iPhone's terrible text to speech. It is the one thing I utterly hate about iPhone. Ive tried apps that try to embed themselves into the iPhone keyboard and they always don't work out well. Hopefully this gets better and we can somehow get it into the iPhone more seamlessly.
    • MayeulC 9 minutes ago
      Speech to text I assume? Maybe it has to do with your a accent or pronunciation? You could contribute a bit to Mozilla's Common voice, if that's the case. I assume it is part of every STT training corpus.
  • grezql 9 minutes ago
    [dead]
  • eethrowaway 7 minutes ago
    [dead]