Whistle: Speech to Text in 16.9 MB

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)!

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 · 31 minutes ago

  Spanish from where? Here (Castilian Spanish) it seemed to work fine.

  • chilicuil · 5 minutes ago

    Mexican and venezuelan aren't detected correctly

  • tecleandor · 3 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.

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.

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 · 22 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...

• boplicity · 5 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.

• testycool · 4 minutes ago

  Unrelated: I love your username.

I initially read this as whistle to text, which would be way cooler.

• mejutoco · 9 minutes ago

  A good project for training an llm https://en.wikipedia.org/wiki/Silbo_Gomero

• charv · 4 minutes ago

  Just like Marvel's Yondu!

Those are insane benchmarks at this size. Well done!

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.

• mrkn1 · 8 minutes ago

  https://github.com/kouhxp/yapsnap/

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.

eager to see if working in android phones

• rpdillon · 5 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/