Earlier quoted context omitted.
Audio synthesis speed is one thing, but is the output _intelligible to a human_ at 1,000wpm? That's the sort of thing Eloquence is being used for, according to the article.
TTS has no intelligence bud. Its only something that transforms text to audio. And that is all that we are talking about here. neither the article or anyone else was discussing the whole stt > llm > tts pipeline.
The state of modern AI text to speech systems for screen reader users
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Re: The state of modern AI text to speech systems for screen reader users
#42This surprises me: "These modern systems are developed to sound human, natural, and conversational. Unfortunately this seems to come at the expense of accuracy. In my testing, both models had a tendency to skip words, read numbers incorrectly, chop off short utterances, and ignore prosody hints from text punctuation. "
They also have built-in abbreviation dictionaries. For example, Acapela likes to expand AST to Atlantic Standard Time, even when the context is so obviously (not) talking about time zones.
Re: The state of modern AI text to speech systems for screen reader users
#43I have been working on playing around with over 10 stt systems in last 25 days and its really weird to read this article as my experience is the opposite. Stt models are amazing today. They are stupid fast, sound great and very simple to implement as huggingface spaces code is readily available for any model. Whats funny is that the model he was talking about "supertonic" was exactly the model I would have recommende…
Just found this video ... it looks to sound and work -very- well. (RasPI & Onyx)
Re: The state of modern AI text to speech systems for screen reader users
#44This almost perfectly encapsulates the problems that create friction for new technology. People want/expect the new technology to be an upgraded version of the old technology. "AI is going to make screen readers amazing!" No, that is not what AI is going to do. That is the exact kind of missing the forest for the trees that comes with new tech. AI will be used to act as a sighted person sitting next to the blind pers…
AI in this sense means using Machine Learning (ML)/Neural Networks (NN) to convert the text (or phonemes) to audio.
There are effectively two approaches to voice synthesis: time-domain and pitch-domain.
In time-domain synthesis you care concatenating short waveforms together. These are variations of Overlap and Add: OLA [1], PSOLA [2], MBROLA [3], etc.
In pitch-domain synthesis, the analysis and synthesis happens in the pitch domain through the Fast Fourier Transform (visualized as a spectrogram [4]), often adjusted to the Mel scale [5] to better highlight the pitches and overtones. The TTS synthesizer is then generating these pitches and converting them back to the time domain.
The basic idea is to extract the formants (pitch bands for the fundamental frequency and overtones) and have models for these. Some techniques include:
1. Klatt formant synthesis [6]
2. Linear Predictive Coding (LPC) [7]
3. Hidden Markov Model (HMM) [8]
4. WaveGrad NN/ML [9]
[1] https://en.wikipedia.org/wiki/Overlap%E2%80%93add_method
[2] https://en.wikipedia.org/wiki/PSOLA -- Pitch-synchronous Overlap and Add
[3] https://en.wikipedia.org/wiki/MBROLA -- Multi-Band Resynthesis Overlap and Add
[4] https://en.wikipedia.org/wiki/Spectrogram
[5] https://en.wikipedia.org/wiki/Mel_scale
[6] https://en.wikipedia.org/wiki/Dennis_H._Klatt
[7] https://en.wikipedia.org/wiki/Linear_predictive_coding
[8] https://www.cs.cmu.edu/~awb/papers/ssw6/ssw6_294.pdf
[9] https://arxiv.org/abs/2009.00713 -- WaveGrad: Estimating Gradients for Waveform Generation
Re: The state of modern AI text to speech systems for screen reader users
#45[dead]
Re: The state of modern AI text to speech systems for screen reader users
#46I have been working on playing around with over 10 stt systems in last 25 days and its really weird to read this article as my experience is the opposite. Stt models are amazing today. They are stupid fast, sound great and very simple to implement as huggingface spaces code is readily available for any model. Whats funny is that the model he was talking about "supertonic" was exactly the model I would have recommende…
Minor nitpick, but you mean "tts" not "stt" both times.
Is supertonic the best sounding model, or is there a different one you'd recommend that doesn't perform as well but sounds even better?
Re: The state of modern AI text to speech systems for screen reader users
#47I have been working on playing around with over 10 stt systems in last 25 days and its really weird to read this article as my experience is the opposite. Stt models are amazing today. They are stupid fast, sound great and very simple to implement as huggingface spaces code is readily available for any model. Whats funny is that the model he was talking about "supertonic" was exactly the model I would have recommende…
Minor nitpick, but you mean "tts" not "stt" both times. Is supertonic the best sounding model, or is there a different one you'd recommend that doesn't perform as well but sounds even better?
yes sorry i mixed these up. supertonic is not the best sounding in my tests. it was by far the fastest, but its audio quality for something so fast was decent. if you wanted something that sounds better AND is also extremely fast pocket tts is the choice. amazing quality and also crazy fast on both gpu and cpu. if you care mainly about quality, chatterbox in my tests was best fit, but its slower then the others. qwen 3 tts was also great but its unisable as any real time agentic voice as its too slow. they havent relesed the code for streaming yet, once they release that this will be my top contender.
Re: The state of modern AI text to speech systems for screen reader users
#48Earlier quoted context omitted.
Minor nitpick, but you mean "tts" not "stt" both times. Is supertonic the best sounding model, or is there a different one you'd recommend that doesn't perform as well but sounds even better?
yes sorry i mixed these up. supertonic is not the best sounding in my tests. it was by far the fastest, but its audio quality for something so fast was decent. if you wanted something that sounds better AND is also extremely fast pocket tts is the choice. amazing quality and also crazy fast on both gpu and cpu. if you care mainly about quality, chatterbox in my tests was best fit, but its slower then the others. qwen…
Thanks!
Re: The state of modern AI text to speech systems for screen reader users
#49Funny I've actually been digging into this problem recently. I have a webaudio reimplementation of Klatt 1980 driven by cmudict. It still sounds pretty ass, but it's very early days. This weekend I intend to go deep dive on the Delta rule system that powers Eloquence. There're so many interesting papers from the late 90s early 2000s I bet we could get something pretty remarkable that sounds even better than Eloquence…
Update: open sourced some fiddling around:
Re: The state of modern AI text to speech systems for screen reader users
#50Earlier quoted context omitted.
Are you using them at 1000 wpm?
Supertonic is probably way faster then that, I wouldn't be surprised if measured it would be something like 14k wpm. On my 4090 I was getting about 175x real time while on cpu only it was 55x realtime. I stopped optimizing it but im sure it could be pushed further. Anyways you should check out their repo to test it yourself its crazy what that team accomplished!
Did you even read the article bud