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Ask HN: What's the current best local/open speech-to-speech setup?

250 points by dsrtslnd23

by d4rkp4ttern

3 subcomments

This is not strictly speech-to-speech, but I quite like it when working with Claude Code or other CLI Agents:
STT: Handy [1] (open-source), with Parakeet V3 - stunningly fast, near-instant transcription. The slight accuracy drop relative to bigger models is immaterial when you're talking to an AI. I always ask it to restate back to me what it understood, and it gives back a nicely structured version -- this helps confirm understanding as well as likely helps the CLI agent stay on track.
TTS: Pocket-TTS [2], just 100M params, and amazing speech quality (English only). I made a voice plugin [3] based on this, for Claude Code so it can speak out short updates whenever CC stops. It uses a non-blocking stop hook that calls a headless agent to create the 1/2-sentence summary. Turns out to be surprisingly useful. It's also fun as you can customize the speaking style and mirror your vibe etc.
The voice plugin gives commands to control it:
```
    /voice:speak stop
    /voice:speak azelma (change the voice)
    /voice:speak <your arbitrary prompt to control the style or other aspects>
```
[1] Handy https://github.com/cjpais/Handy
[2] Pocket-TTS https://github.com/kyutai-labs/pocket-tts
[3] Voice plugin for Claude Code: https://github.com/pchalasani/claude-code-tools?tab=readme-o...

by mpaepper

3 subcomments

You should look into the new Nvidia model: https://research.nvidia.com/labs/adlr/personaplex/
It has dual channel input / output and a very permissible license

by vulkoingim

0 subcomment

I'm using https://spokenly.app/ in local mode, which is free. Very happy with it. It supports a bunch of models, including whisper and parakeet. Right now I'm mostly using parakeet v3 on my desktop, but it tends to do a bit more errors, although it is very fast. I cycle betwen it and Distil-Whisper Large V3.5, which is a bit slower.
On iOS I'm also using the same app, with the Apple Speech model, which I found out to be better performing for me than the parakeet/whisper. One drawback for the apple model is that you need iOS/Mac 26+ - and I haven't bothered to update to Tahoe on my mac.
Both of the models work instantly for me (Mac M1, iphone 17 Pro).
Edit: Aaaand I just saw that you're looking for speech-to-speech. Oops, still sleeping.

by jauntywundrkind

0 subcomment

It was a little annoying getting old qt5 tools installed but I really enjoyed using dsnote / Speech Note. Huge model selection for my amd gpu. Good tool. I haven't done enough specific studying yet to give you suggestions for which model to go with. WhisperFlow is very popular.
Kyutai some very interesting work always. Their delayed streams work is bleeding edge & sounds very promising especially for low latency. Not sure why I have not yet tried it tbh. https://github.com/kyutai-labs/delayed-streams-modeling
There's also a really nice elegant simple app Handy. Only supports Whisper and Parakeet V3 but nice app & those are amazing models. https://github.com/cjpais/Handy

by supermatt

0 subcomment

There was a great post the other day showing low latency end to end using Nvidia models on a single GPU with pipecat
Discussion: https://news.ycombinator.com/item?id=46528045
Article: https://www.daily.co/blog/building-voice-agents-with-nvidia-...

by timwis

1 subcomments

Home Assistant have a fully local voice assistant experience that's very pluggable and customisable. I believe it uses a fast whisper model for STT and piper for TTS.
You can run it on a raspberry pi (or ideally an N100+), and for the microphone/speaker part, you can make your own or buy their off the shelf voice hardware, which works really well.
https://www.home-assistant.io/voice-pe/

by dfajgljsldkjag

2 subcomments

It requires a bit of tinkering, but I think pipecat is the way to go. You can plug in pretty much any STT/LLM/TTS you want and go. It definitely supports local models but its up to you to get your hands on those models.
Not sure if there's any turnkey setups that are preconfigured for local install where you can just press play and go though.
Last I heard E2E speech to speech models are still pretty weak. I've had pretty bad results from gpt-realtime and that's a proprietary model, I'm assuming open source is a bit behind.

by amelius

0 subcomment

For the TTS part: https://github.com/supertone-inc/supertonic

by nsbk

1 subcomments

I'm putting together a streaming ASR + LLM + streaming TTS setup based on Nvidia speech models: nemotron ASR and magpie TTS, pipecat to glue everything together, plus an LLM of your choice. I added Spanish support using canary models, as magpie models are English-only and it still works really well.
The work is based on a repo by pipecat that I forked and modified to be more comfortable to run (docker compose for the server and client), added Spanish support via canary models, and added Nvidia Ampere support so it can run on my 3090.
The use case is a conversation partner for my gf who is learning Spanish, and it works incredibly well. For LLM I settled with Mistral-Small-3.2-24B-Instruct-2506-Q4_K_S.gguf
https://github.com/nsbk/nemotron-january-2026

by andhuman

1 subcomments

I built this recently. I used nvidia parakeet as STT, open wake word as the wake word detection, mistral ministral 14b as LLM and pocket tts for tts. Fits snugly in my 16 gb VRAM. Pocket is small and fast and has good enough voice cloning. I first used the chatterbox turbo model, which perform better and even supported some simple paralinguistic word like (chuckle) that made it more fun, but it was just a bit too big for my rig.

by schobi

2 subcomments

Oh... Having a local-only voice assistant would be great. Maybe someone can share the practical side of this.
Do you have the GPU running all day at 200W to scan for wake words? Or is that running on the machine you are working on anyway?
Is this running from a headset microphone (while sitting at the desk?) or more like a USB speakerphone? Is there an Alexa jailbreak / alternative firmware as a frontend and run this on a GPU hidden away?

by marsbars241

0 subcomment

Tangential: What hardware are you using for the interface on these? Is there a good array microphone that performs on par with echos/ghomes/homepods?

by doonielk

0 subcomment

I did a MLX "streaming ASR + LLM + streaming TTS" pipeline in early 2024. I haven't worked on it since then so it's dated. There are now better versions of all the models I used.
I was able to conversational latency with the ability to interrupt the pipeline on a Mac, using a variety of tricks. It's MLX, so only relevant if you have a Mac.
https://github.com/andrewgph/local_voice
For MLX speech to speech, I've seen:
The mlx-audio package has some MLX implementations of speech to speech models: https://github.com/Blaizzy/mlx-audio/tree/main
kyutai Moshi, maybe old now but has a MLX implementation of their speech to speech model: https://github.com/kyutai-labs/moshi

by beauregardener

0 subcomment

I had this need recently and didn't want to use resource hungry models... so I created this:
https://github.com/caseys/hear-say

by zahlman

0 subcomment

What exactly do you want the pipeline to do that cares about the input being "speech", or indeed that's different from just sending mic -> speaker directly? (I can imagine a few different things, but I want to figure out if your use case sounds like mine, or what suggestions are appropriate for what tasks.)

by varik77

0 subcomment

I have used https://github.com/SaynaAI/sayna . What I like the most is that you can switch between the providers easily and see what works for you the best. It also supports local models.

by sails

1 subcomments

Looking for an iOS app to test this as I’m generally curious about the capabilities of on devices TTS (yet to find an app, but there are loads for text gen)
It can’t be too far off considering Siri and TTS has been on devices for ages

by sgt

2 subcomments

While on this subject, what's the go to transcribe speech to text model (open source or proprietary, doesn't matter) if you have to support a lot of languages really well?

by ripped_britches

1 subcomments

speech to speech is not nearly as good as livekit IMO ("old school" sequence of transcribe, LLM, synthesize). depends on what you're doing of course, but this is just because the LLMs are just way smarter than the speech to speech models which are pretty much the worst (again IMO) at anything beyond basic banter. and livekit is just a framework so you can hook it up with any models in the stack. im not an expert on the local parts but i would assume this pretty easy to glue together.

by hedgehog

0 subcomment

I haven't tried them myself but the Kyutai has a couple projects that could fit.
https://kyutai.org

by Johnny_Bonk

3 subcomments

Anyone using any reasonably good small speech to text os models?

by soulofmischief

0 subcomment

I have a great local assistant that works end-to-end with voice. It's built on local, web-first technologies, it fits small LLMs in memory and manages inference and TTS/STT without stuttering. I've been shaping it up over a couple years and constantly switching out new models.
If you want something simple that runs in browser, look at vosk-browser[0] and vits-web[1].
I'd also recommend checking out KittenTTS[2], I use it and it's great for the size/performance. However, you'd need to implement a custom JavaScript harness for the model since it's a python project. If you need help with that, shoot me an email and I can share some code.
There are other great approaches too if you don't mind python, personally I chose the web as a platform in order to make my agent fully portable and remote once I release it.
And of course, NVIDIA's new model just came out last week[3] but I haven't gotten to test it out just yet, and also there was the recent Sparrow-1[4] announcement which shows people are finally putting money into the problems plaguing voice agents that are rigged up from several models and glue infrastructure, vs a single end-to-end model or at least a conversational turn-taking model to keep things on rails.
[0] https://www.npmjs.com/package/vosk-browser
[1] https://github.com/diffusionstudio/vits-web
[2] https://github.com/KittenML/KittenTTS
[3] https://research.nvidia.com/labs/adlr/personaplex/
[4] https://www.tavus.io/post/sparrow-1-human-level-conversation...

0 subcomment

by DANmode

1 subcomments

https://handy.computer got good marks from a very nontechnical user in my life this week!
Local, FOSS

by masardigital

0 subcomment

good

by bakeryenjoyer

0 subcomment

[dead]

by hackomorespacko

0 subcomment

[flagged]