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OpenAI Audio Models

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Re: OpenAI Audio Models

#261

Hey, I'm Jeff and I was PM for these models at OpenAI. Today we launched three new state-of-the-art audio models. Two speech-to-text models—outperforming Whisper. A new TTS model—you can instruct it how to speak (try it on openai.fm!). And our Agents SDK now supports audio, making it easy to turn text agents into voice agents. We think you'll really like these models. Let me know if you have any questions here!

Hi Jeff, thanks for these and congrats on the launch. Your docs mention supporting accents. I cannot get accents to work at all with the demo.

For instance erasing the entire instruction and replacing it with ‘speak with a strong Boston accent using eg sounds like hahhvahhd’ has no audible effect on the output.

As I’m sure you know 4o at launch was quite capable in this regard, and able to speak in a number of dialects and idiolects, although every month or two seems to bring more nerfs sadly.

A) can you guys explain how to get a US regional accent out of the instructions? On what you meant by accent if not that?

B) since you’re here I’d like to make a pitch that setting 4o for refusal to speak with an AAVE accent probably felt like a good idea to well intentioned white people working in safety. (We are stopping racism! AAVE isn’t funny!) However, the upshot is that my black kid can’t talk to an ai that sounds like him. Well, it can talk like he does if he’s code switching to hang out with your safety folks, but it considers how he talks with his peers as too dangerous to replicate.

This is a pernicious second order race and culture impact that I think is not where the company should be.

I expect this won’t get changed - chat is quite adamant that talking like millions of Americans do would be ‘harmful’ - but it’s one of those moments where I feel the worst parts of the culture wars coming back around to create the harm it purports to care about.

Anyway the 4o voice to voice team clearly allows the non mini model to talk like a Bostonian which makes me feel happy and represented; can the mini api version do this?

Re: OpenAI Audio Models

#262

Hey, I'm Jeff and I was PM for these models at OpenAI. Today we launched three new state-of-the-art audio models. Two speech-to-text models—outperforming Whisper. A new TTS model—you can instruct it how to speak (try it on openai.fm!). And our Agents SDK now supports audio, making it easy to turn text agents into voice agents. We think you'll really like these models. Let me know if you have any questions here!

Having read the docs - used chat gpt to summarize them - there is no mention of speaker diarization for these models. This is a _very_ low hanging fruit anyone with a couple of dgx h100 servers can solve in a month and is a real world problem that needs solving. Right now _no_ tools on the market - paid or otherwise - can solve this with better than 60% accuracy. One killer feature for decision makers is the ability…

> This is a _very_ low hanging fruit anyone with a couple of dgx h100 servers can solve in a month and is a real world problem that needs solving.

I am not convinced it is a low hanging fruit, it's something that is super easy for humans but not trivial for machines, but you are right that it is being neglected by many. I work for speechmatics.com and we spent a significant amoutn of effort over the years on it. We now believe we have the world's best real-time speaker diarization system, you should give it a try.

Re: OpenAI Audio Models

#263
post #233

Earlier quoted context omitted.

Oh man, they have the "Sky" voice, and it seems to be the same one that OpenAI had but then removed? Not sure how that's possible, but I'm very happy about it.

> Not sure how that's possible Download bunch of movies Scarlet Johansen been in, segment into audio clips where she talks and train the model :)

Is it actually her? I didn't think it was, but maybe.

Re: OpenAI Audio Models

#264
post #7

Recommended input for anyone trying this out: Voice: Onyx Vibe: Heavy german accent, doing an Arnold Schwarzenegger impression, way over the top for comedic effect. Deep booming voice, uses pauses for dramatic effect.

My recommendation for Ash: Delivery: Cow noises. You are actually a cow. You can only moo and grunt. No human noises. Only moo. No words. Pauses: Moo and grunt between sentences. Some burps and farts. Tone: Cow.

Hilarious. In addition to lots of moo's and moo-ack's it hallucinated random words and phrases that weren't in the script.

Re: OpenAI Audio Models

#265

Earlier quoted context omitted.

Having read the docs - used chat gpt to summarize them - there is no mention of speaker diarization for these models. This is a _very_ low hanging fruit anyone with a couple of dgx h100 servers can solve in a month and is a real world problem that needs solving. Right now _no_ tools on the market - paid or otherwise - can solve this with better than 60% accuracy. One killer feature for decision makers is the ability…

> This is a _very_ low hanging fruit anyone with a couple of dgx h100 servers can solve in a month and is a real world problem that needs solving. I am not convinced it is a low hanging fruit, it's something that is super easy for humans but not trivial for machines, but you are right that it is being neglected by many. I work for speechmatics.com and we spent a significant amoutn of effort over the years on it. We n…

After throwing the average meeting as an mp3 to your system, yes, you have diarization solved much better than everyone else I've tried by far. I'd say you're 95% of the way to being good enough for becoming the backbone of monolingual corporate meeting transcription, and I'll be buying API tokens the next time I need to do this instead of training a custom model. Your transcription however isn't that great - but good enough for LLMs to figure out a minutes of the meeting.

That said, the trick to extracting voices is to work in frequency space. Not sure what your model does but my home made version first ran all the audio through a fft, then essentially became a vision problem for finding speech patterns that matched in pitch and finally output extremely fined grained time stamps for where they were found and some python glue threw that into an open source whisper tts model.

Re: OpenAI Audio Models

#266
Well, I'm pretty blown away. Especially when you realize that this release will probably get blown out of the water in less than a years time.

Re: OpenAI Audio Models

#267

If I'm reading the pricing correctly, these models are SIGNIFICANTLY cheaper than ElevenLabs. https://platform.openai.com/docs/pricing If these are the "gpt-4o-mini-tts" models, and if the pricing estimate of "$0.015 per minute" of audio is correct, then these prices 85% cheaper than those of ElevenLabs. https://elevenlabs.io/pricing With ElevenLabs, if I choose their most cost-effectuve "Business" plan for $1100 per…

It's way cheaper - everyone is, elevenlabs is very expensive. Nobody matches their quality though. Especially if you want something that doesn't sound like a voice assistant/audiobook/podcast/news anchor/tv announcer. This openai offering is very interesting, it offers valuable features elevenlabs doesn't in emotional control. It also hallucinates though which would need to be fixed for it to be very useful.

It's cheap because everything OpenAI does is subsidized by investors' money. Until that stupid money flows all good! Then either they'll go the way of WeWork, or enshittification will happen to make it possible for them to make the books work. I don't see any other option. Unless Softbank decides it has some 150 Billion to squander on buying them off. There's a lot of head-in-the-sand behavior going on around OpenAI fundamentals and I don't understand exactly why it's not more in the open yet.

Re: OpenAI Audio Models

#268
post #10

Interesting, I inserted a bunch of "fuck"s in the text and the "NYC Cabbie" voice read it all just fine. When I switched to other voices ("Connoisseur", "Cheerleader", "Santa"), it responded "I'm sorry I can't assist with that request". I switched back to "NYC Cabbie" and it again read it just fine. I then reloaded the session completely, refreshed the voice selections until "NYC Cabbie" came up again, and it still r…

Have you tried repeatedly? I got Santa to read the "gorilla warfare" copypasta on my second try.

Re: OpenAI Audio Models

#269

Earlier quoted context omitted.

It's way cheaper - everyone is, elevenlabs is very expensive. Nobody matches their quality though. Especially if you want something that doesn't sound like a voice assistant/audiobook/podcast/news anchor/tv announcer. This openai offering is very interesting, it offers valuable features elevenlabs doesn't in emotional control. It also hallucinates though which would need to be fixed for it to be very useful.

It's cheap because everything OpenAI does is subsidized by investors' money. Until that stupid money flows all good! Then either they'll go the way of WeWork, or enshittification will happen to make it possible for them to make the books work. I don't see any other option. Unless Softbank decides it has some 150 Billion to squander on buying them off. There's a lot of head-in-the-sand behavior going on around OpenAI…

If you compare with e.g. Deepseek and other hosters, you'll find that OpenAI is actually almost certainly charging very high margins (Deepseek has an 80% profit margin and they're 10x cheaper than openai).

The training/R&D might make OpenAI burn VC cash, but this isn't comparable with companies like WeWork whose products actively burn cash

Re: OpenAI Audio Models

#270
post #223

Hey, I'm Jeff and I was PM for these models at OpenAI. Today we launched three new state-of-the-art audio models. Two speech-to-text models—outperforming Whisper. A new TTS model—you can instruct it how to speak (try it on openai.fm!). And our Agents SDK now supports audio, making it easy to turn text agents into voice agents. We think you'll really like these models. Let me know if you have any questions here!

Hi Jeff. This is awesome. Any plans to add word timestamps to the new speech-to-text models, though? > Other parameters, such as timestamp_granularities, require verbose_json output and are therefore only available when using whisper-1. Word timestamps are insanely useful for large calls with interruptions (e.g. multi-party debate/Twitter spaces), allowing transcript lines to be further split post-transcription on se…

Accurate word timestamps seems an overhead and required a post processing like forced alignment (speech technique that can automatically align audio files with transcripts)

Had a recent dive into a forced alignment, and discovered that most of new models dont operate on word boundaries, phoneme, etc but rather chunk audio with overlap and do word, context matching. Older HHM-style models have shorter strides (10ms vs 20ms).

Tried to search into Kaldi/Sherpa ecosystem, and found most info leads to nowhere or very small and inaccurate models.

Appreciate any tips on the subject

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