My understanding is that this is purely a strategic choice by the bigger labs. When OpenAI released Whisper, it was by far best-in-class, and they haven't released any major upgrades since then. It's been 3.5 years... Whisper is older than ChatGPT.
Gemini 3 Pro Preview has superlative audio listening comprehension. If I send it a recording of myself in a car, with me talking, and another passenger talking to the driver, and the radio playing, me in English, the radio in Portuguese, and the driver+passenger in Spanish, Gemini can parse all 4 audio streams as well as other background noises and give a translation for each one, including figuring out which voice belongs to which person, and what everyone's names are (if it's possible to figure that out from the conversation).
I'm sure it would have superlative audio generation capabilities too, if such a feature were enabled.
It's amazing how good open-weight STT and TTS have gotten, so there's no need to pay for Wispr Flow, Superwhisper, Eleven-Labs etc.
Sharing my setup in case it may be useful for others; it's especially useful when working with CLI agents like Code Code or Codex-CLI:
STT: Hex [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. It is a MacOS native app and leverages the CoreML/Neural Engine to get extremely fast transcription (I used to recommend a similar app Handy but it has frequent stuttering issues, and Hex is actually even faster, which I didn't think was possible!)
TTS: Kyutai's 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 combination of hooks that nudge the main agent to append a speakable summary, falling back to using a headless agent in case the main agent forgets. Turns out to be surprisingly useful. It's also fun as you can customize the speaking style and mirror your vibe and "colorful language" etc.
The voice plugin gives commands to control it:
/voice:speak stop
/voice:speak azelma (change the voice)
/voice:speak prompt <your arbitrary prompt to control the style>
Good article and I agree with everything in there. For my own voice agent I decided to make him PTT by default as the problems of the model accurately guessing the end of utterance are just too great. I think it can be solved in the future but, I haven't seen a really good example of it being done with modern day tech including this labs. Fundamentally it all comes down to the fact that different humans have different ways of speaking, and the human listening to them updates their own internal model of the speech pattern. Adjusting their own model after a couple of interactions and arriving at the proper way of speaking with said person. Something very similar will need to be done and at very fast latency's for it to succeed in the audio ml world. But I don't think we have anything like that yet. It seems currently best you can do is tune the model on a generic speech pattern that you expect to fit over a larger percentage of the human population and that's about the best you can do, anyone who falls outside of that will feel the pain of getting interrupted every time.
OpenAI and google are too scared of music industry lawyers to tackle this. Internally they without a doubt have models that would crush these startups over night if they chose to release them.
Is your claim that music industry lawyers are that much scarier than movie industry lawyers? Because the big labs don't seem to have any problem releasing models that create (possibly infringing) video.
I'm not sure it's just fear of lawyers, although that's definitely part of it. Big companies have way more to lose reputationally and legally, so the bar for releasing something is much higher
OpenAI being the death star and audio AI being the rebels is such a weird comparison, like what? Wouldn't the real rebels be the ones running their own models locally?
Audio AI companies are just another death star, intent on reducing human creativity to "make a song like Let it be, but in the style of Eminem, and change the lyrics to match the birthday of my mother in law". The only rebels are musicians resisting this hedge-fund driven monstrosity.
True, but there's a fun irony: the Rebels' X-Wings are powered by GPUs from a company that's... checks relationships ...also supplying the Empire.
NVIDIA's basically the galaxy's most successful arms dealer, selling to both sides while convincing everyone they're just "enabling innovation." The real rebels would be training audio models on potato-patched RP2040s. Brave souls, if they exist.
Speaking of audio + AI, here's a "learning hack" I've been trying with voice mode, and the 3 big AI labs still haven't nailed it:
While on a walk with mobile phone + earphones, dump an article/paper/HN-Post/github-repo into the mobile chat app (chat-gpt, claude or gemini), and use voice mode to have it walk you through it conversationally, so you can ask follow up questions during the walk-thru and the AI would do web-search etc. I know I could do something like this with NotebookLM, but I want to engage in the conversation, and NotebookLM does have interactive mode but it has been super-flaky to say the least.
I pay for ChatGPT Pro and the voice mode is really bad: it pretends to do web searches and makes up things, and when pushed says it didn't actually read the article. Also the voice sounds super-condescending.
Gemini Pro mobile app - similarly refuses to open links and sounds as if it's talking to a baby.
Claude mobile app was the best among these - the voice is very tolerable in terms of tone, but like the others it can't open links. I does do web searches, but gets some type of summaries of pages, and it doesn't actually go into the links themselves to give me details.
I have found that the "advanced voice mode" is dumb as a box of rocks compared to their "basic" TTS version, so I disable it. I've switched to Claude, so I don't know if that's still an option, but if you are tied to ChatGPT, definitely disable it if possible!
Audio models are also tiny, which is probably why small labs are doing well in the space. I run a LoRA'd Whisper v3 Large for a client. We can fit 4 versions of the model in memory at once on a ~$1/hr A10 and have half the VRAM leftover.
Each of the LoRA tunes we did took maybe 2-3 hours on the same A10 instance.
I check every day for a new full-duplex model. I was so hyped about PersonaPlex from their demos, but in my test it was oddly dumb and unable to follow instructions.
So I am hoping for something like PersonaPlex but a bit larger.
Has anyone tested MiniCPM-o?.How is it at instruction following?
Moshi was an amazing tech demo, building the entire stack from scratch in 6 months with a small team was an amazing show of skill: 7B text LLM data + training, emotive TTS for synth data generation (again model + data collection), synth data pipeline, novel speech codec, rust inference stack for low latency, audio LLM architecture incl. text "thoughts" stream which was novel.
But, this piece is a fluff piece: "underfunded" means a total of around $400 million ($330 million in the initial round, $70 million for Gradium). Compare to Elevenlabs who used a $2 million pre-seed for creating their initial product.
A bunch of other stuff there is disingenuous, like comparing their 7B model to Llama-3 405B (hint: the 7B model is a _lot_ dumber). There's also the outright lie: team of 4 made Moshi, which is corrected _in the same piece_ to 8 if you read enough.
I was suspicious that they are not mentioned, but then I realized this is a VC opinion piece and the first company mentioned joined their portfolio last year.
Can someone reccomend to me: a service that will generate a loopable engine drone for a "WWII Plane Japan Kawasaki Ki-61"? It doesn't have to be perfect, just convincing in a hollywood blockbuster context, and not just a warmed over clone of a Merlin engine sound. Turns out Suno will make whatever background music I need, but I want a "unique sound effect on demand" service. I'm not convinced voice AI stuff is sustainable
With the prompt "WWII Plane Japan Kawasaki Ki-61 flying by, propeller airplane" and setting looping on and 30 sec duration manually instead of auto (the duration predictor fails pretty bad at this prompt, you need to be logged in to set duration manually) it works pretty well. No idea if it's close to that specific airplane though it sounds like a ww2 plane to me though.
Most current "voice assistants" still feel like glorified walkie-talkies... you talk, pause awkwardly, they respond, and any interruption breaks the flow
I use the standard iPhone TTS accessibility tool and an iOS ebook reader.
It has modern voices, but I prefer the robotic voice from 15 years ago because it's very patterned and predictable, which makes it easier to follow at super-fast speaking rates -- something closer to my visual reading rate.
Transcription providers like wisprflow and willow voice are
typically providing nice UI/UX around open source models.
Wisprflow does not create it's own models but i know willow voice did do extensive finetuning to improve the quality and speed of their transcription models so you may count them.
Right now small labs also have the best chance at tool harness improvements, which can yield just as many gains in AI performance as model training research.
Hey Rob. I'm not on the tech team here at Gradium (I do GTM) but still curious where you found the glitch? Were you entering words into the STT in the bottom of the front page? Can you share an example so I can replicate? Many thanks!
Also, while the author complains that there is not a lot of high quality data around [0], you do not need a lot of data to train small models. Depending on the problem you are trying to solve, you can do a lot with single-digit gigabytes of audio data. See, e.g., https://jmvalin.ca/demo/rnnoise/
[0] Which I do agree with, particularly if you need it to be higher quality or labeled in a particular way: the Fisher database mentioned is narrowband and 8-bit mu-law quantized, and while there are timestamps, they are not accurate enough for millisecond-level active speech determination. It is also less than 6000 conversations totaling less than 1000 hours (x2 speakers, but each is silent over half the time, a fact that can also throw a wrench in some standard algorithms, like volume normalization). It is also English-only.
I refuse to believe that none of these people ever heard of Nyquist, and that noone was able to come up with "ayyy lmao let's put a low pass on this before downsampling".
Edit: 2 day old account posting stuff that doesn't pass the sniff test. Hmmmm... baited by a bot?
Taek|14 days ago
Gemini 3 Pro Preview has superlative audio listening comprehension. If I send it a recording of myself in a car, with me talking, and another passenger talking to the driver, and the radio playing, me in English, the radio in Portuguese, and the driver+passenger in Spanish, Gemini can parse all 4 audio streams as well as other background noises and give a translation for each one, including figuring out which voice belongs to which person, and what everyone's names are (if it's possible to figure that out from the conversation).
I'm sure it would have superlative audio generation capabilities too, if such a feature were enabled.
nickpsecurity|13 days ago
d4rkp4ttern|14 days ago
Sharing my setup in case it may be useful for others; it's especially useful when working with CLI agents like Code Code or Codex-CLI:
STT: Hex [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. It is a MacOS native app and leverages the CoreML/Neural Engine to get extremely fast transcription (I used to recommend a similar app Handy but it has frequent stuttering issues, and Hex is actually even faster, which I didn't think was possible!)
TTS: Kyutai's 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 combination of hooks that nudge the main agent to append a speakable summary, falling back to using a headless agent in case the main agent forgets. Turns out to be surprisingly useful. It's also fun as you can customize the speaking style and mirror your vibe and "colorful language" etc.
The voice plugin gives commands to control it:
[1] Hex https://github.com/kitlangton/Hex[2] Pocket-TTS https://github.com/kyutai-labs/pocket-tts
[3] Voice plugin for Claude Code: https://pchalasani.github.io/claude-code-tools/plugins-detai...
andhuman|13 days ago
freedomben|14 days ago
aidenn0|13 days ago
nowittyusername|14 days ago
spuz|14 days ago
https://www.tavus.io/post/sparrow-0-advancing-conversational...
KurSix|14 days ago
dkarp|14 days ago
United857|14 days ago
echelon|14 days ago
They'll optimize down the stack once they've sucked all the oxygen out of the room.
Little players won't be able to grow through the ceiling the giants create.
qoez|14 days ago
WJW|14 days ago
amelius|14 days ago
KurSix|14 days ago
giancarlostoro|14 days ago
tgv|14 days ago
tl2do|14 days ago
NVIDIA's basically the galaxy's most successful arms dealer, selling to both sides while convincing everyone they're just "enabling innovation." The real rebels would be training audio models on potato-patched RP2040s. Brave souls, if they exist.
wavemode|14 days ago
lukax|14 days ago
https://www.daily.co/blog/benchmarking-stt-for-voice-agents/
beaker52|14 days ago
They’ll wait for progress to be made and then buy the capability/expertise/talent when the time is right.
d4rkp4ttern|13 days ago
While on a walk with mobile phone + earphones, dump an article/paper/HN-Post/github-repo into the mobile chat app (chat-gpt, claude or gemini), and use voice mode to have it walk you through it conversationally, so you can ask follow up questions during the walk-thru and the AI would do web-search etc. I know I could do something like this with NotebookLM, but I want to engage in the conversation, and NotebookLM does have interactive mode but it has been super-flaky to say the least.
I pay for ChatGPT Pro and the voice mode is really bad: it pretends to do web searches and makes up things, and when pushed says it didn't actually read the article. Also the voice sounds super-condescending.
Gemini Pro mobile app - similarly refuses to open links and sounds as if it's talking to a baby.
Claude mobile app was the best among these - the voice is very tolerable in terms of tone, but like the others it can't open links. I does do web searches, but gets some type of summaries of pages, and it doesn't actually go into the links themselves to give me details.
TheTaytay|13 days ago
unknown|14 days ago
[deleted]
AustinDev|14 days ago
Each of the LoRA tunes we did took maybe 2-3 hours on the same A10 instance.
freedomben|14 days ago
ilaksh|13 days ago
So I am hoping for something like PersonaPlex but a bit larger.
Has anyone tested MiniCPM-o?.How is it at instruction following?
pain_perdu|13 days ago
shenberg|14 days ago
But, this piece is a fluff piece: "underfunded" means a total of around $400 million ($330 million in the initial round, $70 million for Gradium). Compare to Elevenlabs who used a $2 million pre-seed for creating their initial product.
A bunch of other stuff there is disingenuous, like comparing their 7B model to Llama-3 405B (hint: the 7B model is a _lot_ dumber). There's also the outright lie: team of 4 made Moshi, which is corrected _in the same piece_ to 8 if you read enough.
Miraltar|14 days ago
bossyTeacher|14 days ago
gorgoiler|14 days ago
krackers|14 days ago
[1] https://en.wikipedia.org/wiki/15.ai
hadlock|14 days ago
almostdigital|14 days ago
With the prompt "WWII Plane Japan Kawasaki Ki-61 flying by, propeller airplane" and setting looping on and 30 sec duration manually instead of auto (the duration predictor fails pretty bad at this prompt, you need to be logged in to set duration manually) it works pretty well. No idea if it's close to that specific airplane though it sounds like a ww2 plane to me though.
djmips|13 days ago
nextaccountic|14 days ago
https://elevenlabs.io/sound-effects
KurSix|14 days ago
fainpul|13 days ago
nerevarthelame|13 days ago
It has modern voices, but I prefer the robotic voice from 15 years ago because it's very patterned and predictable, which makes it easier to follow at super-fast speaking rates -- something closer to my visual reading rate.
bilater|13 days ago
yismail|13 days ago
joshmlewis|13 days ago
gmerc|14 days ago
amelius|14 days ago
mrbluecoat|14 days ago
..plenty of money to be made elsewhere
lysace|14 days ago
Audio is too niche and porn is too ethically messy and legally risky.
There's also music, which the giants also don't touch. Suno is actually really impressive.
SilverElfin|14 days ago
carshodev|14 days ago
Wisprflow does not create it's own models but i know willow voice did do extensive finetuning to improve the quality and speed of their transcription models so you may count them.
znnajdla|13 days ago
RobMurray|14 days ago
You get all kinds of weird noises and random words. Jack is often apologetic about the problem you are having with the Hyperion xt5000 smart hub.
pain_perdu|14 days ago
umairnadeem123|14 days ago
[deleted]
throwjjj|14 days ago
[deleted]
lennexz|14 days ago
[deleted]
anvevoice|14 days ago
[deleted]
tl2do|14 days ago
[deleted]
derf_|14 days ago
[0] Which I do agree with, particularly if you need it to be higher quality or labeled in a particular way: the Fisher database mentioned is narrowband and 8-bit mu-law quantized, and while there are timestamps, they are not accurate enough for millisecond-level active speech determination. It is also less than 6000 conversations totaling less than 1000 hours (x2 speakers, but each is silent over half the time, a fact that can also throw a wrench in some standard algorithms, like volume normalization). It is also English-only.
isoprophlex|14 days ago
Edit: 2 day old account posting stuff that doesn't pass the sniff test. Hmmmm... baited by a bot?
jlehrer1|14 days ago
[deleted]
nubg|14 days ago
[deleted]
duped|14 days ago
anvevoice|14 days ago
[deleted]
bstsb|13 days ago
(source: just look at their comment history)