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Show HN: Moonshine Open-Weights STT models – higher accuracy than WhisperLargev3

I wanted to share our new speech to text model, and the library to use them effectively. We're a small startup (six people, sub-$100k monthly GPU budget) so I'm proud of the work the team has done to create streaming STT models with lower word-error rates than OpenAI's largest Whisper model. Admittedly Large v3 is a couple of years old, but we're near the top the HF OpenASR leaderboard, even up against Nvidia's Parakeet family. Anyway, I'd love to get feedback on the models and software, and hear about what people might build with it.

According to the OpenASR Leaderboard [1], looks like Parakeet V2/V3 and Canary-Qwen (a Qwen finetune) handily beat Moonshine. All 3 models are open, but Parakeet is the smallest of the 3. I use Parakeet V3 with Handy and it works great locally for me.

[1]: https://huggingface.co/spaces/hf-audio/open_asr_leaderboard

6 hours agoKarrot_Kream

Parakeet V3 is over twice the parameter count of Moonshine Medium (600m vs 245m), so it's not an apples to apples comparison.

I'm actually a little surprised they haven't added model size to that chart.

4 hours agoreitzensteinm

So I'm kinda new to this whole parakeet and moonshine stuff, and I'm able to run parakeet on a low end CPU without issues, so I'm curious as to how much that extra savings on parameters is actually gonna translate.

Oh and I type this in handy with just my voice and parakeet version three, which is absolutely crazy.

5 minutes agoagentifysh

By the way, I've been using a Whisper model, specifically WhisperX, to do all my work, and for whatever reason I just simply was not familiar with the Handy app. I've now downloaded and used it, and what a great suggestion. Thank you for putting it here, along with the direct link to the leaderboard.

I can tell that this is now definitely going to be my go-to model and app on all my clients.

4 hours agotheologic

I have to ask- I see this handy app running on Mac and you hold a key down and then it doesn't show until seemingly a while later.

The one built in is much faster, and you only have to toggle it on.

Are these so much more accurate? I definitely have to correct stuff, but pretty good experience.

Also use speech to text on my iphone which seems to be the same accuracy.

an hour agojasonjmcghee

Handy is amazing. Super quality app.

2 hours agotuananh

It really is. It's kinda ridiculous that it's free.

7 minutes agoagentifysh

hmmm looks like assembyAI is still unbeatable here in terms of cost/performance unless im mistaken

edit: holy shit parakeet is good.... Moonshine impressive too and it is half the param

Now if only there was something just as quick as Parakeet v3 for TTS ! Then I can talk to codex all day long!!!

an hour agoagentifysh

Parakeet doesn't require a GPU. I'm handily running it on my Ubuntu Linux laptop.

an hour agoremuskaos

you are right i just downloaded it on handy and its working i can't believe it

i was using assmeblyAI but this is fast and accurate and offline wtf!

an hour agoagentifysh

How much VRAM does parakeet take for you? For some reason it takes 4GB+ for me using the onyx version even though it’s 600M parameters

4 hours agosyntaxing

why V3 over V2 (assuming English only)?

3 hours agotomr75

Claiming higher accuracy than Whisper Large v3 is a bold opening move. Does your evaluation account for Whisper's notorious hallucination loops during silences (the classic 'Thank you for watching!'), or is this purely based on WER on clean datasets? Also, what's the VRAM footprint for edge deployments? If it fits on a standard 8GB Mac without quantization tricks, this is huge.

3 hours agoheftykoo

Nice work. One metric I’d really like to see for streaming use cases is partial stability, not just final WER.

For voice agents, the painful failure mode is partials getting rewritten every few hundred ms. If you can share it, metrics like median first-token latency, real-time factor, and "% partial tokens revised after 1s / 3s" on noisy far-field audio would make comparisons much more actionable.

If those numbers look good, this seems very promising for local assistant pipelines.

2 hours agoguerython

I've helped many Twitch streamers set up https://github.com/royshil/obs-localvocal to plug transcription & translation into their streams, mainly for German audio to English subtitles.

I'd love a faster and more accurate option than Whisper, but streamers need something off-the-shelf they can install in their pipeline, like an OBS plugin which can just grab the audio from their OBS audio sources.

I see a couple obvious problems: this doesn't seem to support translation which is unfortunate, that's pretty key for this usecase. Also it only supports one language at a time, which is problematic with how streamers will frequently code-switch while talking to their chat in different languages or on Discord with their gameplay partners. Maybe such a plugin would be able to detect which language is spoken and route to one or the other model as needed?

4 hours agofrancislavoie

Any plans regarding JavaScript support in the browser?

There was an issue with a demo but it's missing now. I can't recall for sure but I think I got it working locally myself too but then found it broke unexpectedly and I didn't manage to find out why.

5 hours agonmstoker

Accuracy is often presumed to be english, which is fine, but it's a vague thing to say "higher" because does it mean higher in English only? Higher in some subset of languages? Which ones?

The minimum useful data for this stuff is a small table of language | WER for dataset

5 hours agofareesh
[deleted]
an hour ago

This is awesome, well done guys, I’m gonna try it as my ASR component on the local voice assistant I’ve been building https://github.com/acatovic/ova. The tiny streaming latencies you show look insane

6 hours agoarmcat

No idea why 'sudo pip install --break-system-packages moonshine-voice' is the recommended way to install on raspi?

The authors do acknowledge this though and give a slightly too complex way to do this with uv in an example project (FYI, you dont need to source anything if you use uv run)

6 hours agoac29

Very cool. Anyway to run this in Web assembly, I have a project in mind

5 hours ago999900000999

For those wondering about the language support, currently English, Arabic, Japanese, Korean, Mandarin, Spanish, Ukrainian, Vietnamese are available (most in Base size = 58M params)

6 hours agoasqueella

Implemented this to transcribe voice chat in a project and the streaming accuracy in English on this was unusable, even with the medium streaming model.

3 hours agostarkparker

haven't tested yet but I'm wondering how it will behave when talking about many IT jargon and tech acronyms. For those reason I had to mostly run LLM after STT but that was slowing done parakeet inference. Otherwise had problems to detect properly sometimes when talking about e.g. about CoreML, int8, fp16, half float, ARKit, AVFoundation, ONNX etc.

6 hours agopzo

Do you also support timestamps the detected word or even down to characters?

2 hours agooezi

Streaming transcription is crazy fast on an M1. Would be great to use this as a local option versus Wispr Flow.

4 hours agosaltwounds

How does this compare to Parakeet, which runs wonderfully on CPU?

6 hours agog-mork

fyi the typepad link in your bio is broken

2 hours agoraybb

onnx models for browser possible?

6 hours agosroussey

If only it did Doric

5 hours agoalexnewman

No LICENSE no go

7 hours agocyanydeez

There is a license blurb in the readme.

> This code, apart from the source in core/third-party, is licensed under the MIT License, see LICENSE in this repository.

> The English-language models are also released under the MIT License. Models for other languages are released under the Moonshine Community License, which is a non-commercial license.

> The code in core/third-party is licensed according to the terms of the open source projects it originates from, with details in a LICENSE file in each subfolder.

7 hours agobangaladore

The LICENSE file that refers to is missing. There's one in the python folder, but not for the rest of the code.

4 hours agomkl

reading through readme.md "License This code, apart from the source in core/third-party, is licensed under the MIT License, see LICENSE in this repository.

The English-language models are also released under the MIT License. Models for other languages are released under the Moonshine Community License, which is a non-commercial license.

The code in core/third-party is licensed according to the terms of the open source projects it originates from, with details in a LICENSE file in each subfolder."

7 hours agoaltruios