clayhacks
I made a little python wrapper around it to serve an HTTP
endpoint that's OpenAI/elevenlabs compatible
https://github.com/clayrosenthal/bootlegger
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sgt
Quick link to the video where he demos it:
https://www.youtube.com/watch?v=kMliOFYBiz4
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> 8bitsrule
Thanks for that ... impressive!
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senkora
Wow, it seems like this might beat out flite for
very-low-memory TTS? I ended up abandoning a project of
mine because I couldn't get high enough quality or low
enough memory usage out of flite, so I'm very excited to
try this out.Flite for comparison:
https://github.com/festvox/flite
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jedberg
Do you have any accuracy benchmarks?I've worked in this
space. TTS in a small footprint isn't the hard part --
it's doing it accurately that's hard.Although for the use
cases OP is targeting, lower accuracy may be good enough!
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> amelius
> I've worked in this space. TTS in a small footprint
isn't the hard part -- it's doing it accurately that's
hard.This actually holds for everything in AI.
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> kamranjon
If you look at this chart here it seems the tiny model
has a WER of ~12%... not sure about the micro
model:https://github.com/moonshine-ai/moonshine#when-s
hould-you-ch...
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> > yorwba
That's the error rate for STT, not TTS. TTS is
generally easier than STT because you only need to
produce one valid pronunciation and don't need to
handle variation within and between individuals.
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orliesaurus
I installed the command line version using uv uv init
uv add moonshine-voice
uv run moonshine-voice mic --language en
super nice to be able to run it to test it like thisgood
job on a clear readme.md tbh
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> pwgawron
`uvx moonshine-voice mic --language en` That is even
simpler.
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smcameron
For TTS I wonder how this compares to nanotts[1] with the
en-GB voice, which is sort of unreasonably good.[1]
https://github.com/gmn/nanotts
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gitgud
So at that tiny 500kb size I imagine it could be compiled
to web assembly, and run entirely in the browser
right?Couldn't find a link, is that hard to do?
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> hahahaa
500k memory but not sure about disk.
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userbinator
This looks like an extreme point for AI-based TTS, as
formant/tract modeling synths tend to be more accurate if
you want TTS in a tiny amount of compute, but sound
distinctly robotic.TTS (neural diphone synth @ 16 kHz)
~1.8 MiB voice packThis is in the realm of Microsoft Sam.
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> HarHarVeryFunny
Presumably it's not, but the TTS voice in the video
sounds to me more like formant synthesis than diphone
- it reminds me of my DECtalk.The project credits does
mention espeak (which is formant based) as well as
various other TTS projects, although it sounds like
they are only using the pronunciation part of espeak,
not the voice
synthesis.https://github.com/moonshine-ai/moonshine#ac
knowledgements
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stfurkan
It looks great, thank you! I'll see if I can use it for my
in browser AI assistant project's ( https://aidekin.com )
voice part. It's currently using Nemotron-3.5-ASR and
supertonic-3 but overall it requires 1.2gb download.
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walrus01
Given the tiny size of this, I wonder about possible
future integration with esphome compatible
hardwarehttps://esphome.io/
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> KennyBlanken
I suppose, but for home automation, esps are best for
getting the audio to something more powerful. If this
lets a raspberry pi do voice recognition really fast,
that alone is worth it.
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dwa3592
this is good to see. i also trained a stt under 500kb for
sub dollar chips. it had about 20 words that it could
understand(like start, stop, left, right, go, up etc) and
then the spell mode where you could say the word spell and
then say the individual english alphabets and close with
spell. it was super fun to work on. these tend to be
extremely unstable though, like confusion between p and t
(at least for my accent). will have to try this one now.
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> NooneAtAll3
I remember someone training smart kettle to use its
speaker as microphone
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> laidoffamazon
IIRC the Alexa enabled voice remotes also used a
similarly small model though perhaps not this small
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t0mpr1c3
Very cool. I've done TTS on a 32K Arduino but it was
pretty croaky. https://youtu.be/ErGDboTpwM0
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jjcm
The voice activity detection alone here is compelling -
very useful for doing things like highlighting a speaker
who's transmitting in realtime. At that rate the impact on
perf will be so minimal that you could easily run it in
the browser across devices.
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nserrino
Voice is one of the most latency-sensitive modalities in
AI. Moonshine is doing awesome stuff
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zarmin
Thank you for this. I love your work on Curb Your
Enthusiasm.
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> > shermantanktop
Possibly Cousin Andy?
https://curb-your-enthusiasm.fandom.com/wiki/Andy_
DavidPlayed by the great Richard Kind, who my wife
swears she saw on the Highline in NYC.
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> > stavros
Probably a joke that the author looks like someone
on the show? I'm puzzled as well.
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0xnyn
ngl, it looks incredible
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