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

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

#21

Post by francislavoie »

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?

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

#22

Post by theologic »

Karrot_Kream wrote: post #12

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

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.

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

#23

Post by syntaxing »

Karrot_Kream wrote: post #12

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

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

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

#24

Post by mkl »

bangaladore wrote: post #3
cyanydeez wrote: post #2

No LICENSE no go

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…

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

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

#25

Post by tomr75 »

Karrot_Kream wrote: post #12

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

why V3 over V2 (assuming English only)?

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

#27

Post by heftykoo »

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.

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

#29

Post by tuananh »

Karrot_Kream wrote: post #12

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

Handy is amazing. Super quality app.
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