TensorFlowTTS
Thorsten-Voice
| TensorFlowTTS | Thorsten-Voice | |
|---|---|---|
| 6 | 1 | |
| 3,702 | 482 | |
| 0.9% | - | |
| 0.0 | 6.4 | |
| 5 months ago | 3 months ago | |
| Python | Python | |
| Apache License 2.0 | Creative Commons Zero v1.0 Universal |
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TensorFlowTTS
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Ask HN: On-Device Text to Speech
Hey HN, has anyone found a viable solution for doing this locally and offline on iOS? I'd like to offer a privacy-friendly text to speech feature to my App, and Apple's speech synthesis sounds awful compared to some newer models and TTS engines. The only thing I've found is an older TensorflowTTS example here: https://github.com/TensorSpeech/TensorFlowTTS/tree/master/examples/ios
Any pointers or tips appreciated.
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NaturalSpeech: End-to-End Text to Speech Synthesis with Human-Level Quality
I had a lot of success using [FastSpeech2 + MB MelGAN via TensorFlowTTS](https://github.com/TensorSpeech/TensorFlowTTS). There are demos for [iOS](https://github.com/TensorSpeech/TensorFlowTTS/tree/master/ex...) and [Android](https://github.com/TensorSpeech/TensorFlowTTS/tree/master/ex...) which will allow you to run pretty convincing, modern TTS models with only a few hundred milliseconds of processing latency.
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TTS mobile help
I need an example of how I would go about it. I've combed through examples but it's just not clicking for me.
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A Working TTS feature has been found (No Google Services Required)
https://github.com/TensorSpeech/TensorFlowTTS was the project. It was pretty much a direct compile and run. I went through and added the required features to enable it as TTS service for Android. I also moved the Tensorflow portion into a separate thread from the TTS service directly, since Android restricts it's TTS service to a single thread, and the Tensorflow service uses five threads to run at a good speed. It's a much much heavier solution than a C/C++ compiled library, but it works out of the box and I will worry about optimizations later
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Free library for text-to-speech
You need to try, it implements most advanced algorithms and not as ad-hoc as nvidia https://github.com/TensorSpeech/TensorFlowTTS
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Reviving the 1973 Unix text to voice translator
For open source offline TTS with more or less recent algorithms you can check
https://github.com/TensorSpeech/TensorFlowTTS
Thorsten-Voice
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NaturalSpeech: End-to-End Text to Speech Synthesis with Human-Level Quality
For german users, I can recommend to take a look at
https://www.thorsten-voice.de/
https://github.com/thorstenMueller/Thorsten-Voice
where someone contributed a huge set of his voice samples and a tutorial / script collection to build a pretty decent TTS model LOCALLY.
Quality-wise it is not that good, but its free and pretty easy to follow for a tech enthusiast.
What are some alternatives?
tortoise-tts - A multi-voice TTS system trained with an emphasis on quality
opentts - Open Text to Speech Server
TTS - :robot: :speech_balloon: Deep learning for Text to Speech (Discussion forum: https://discourse.mozilla.org/c/tts)
nerd-dictation - Simple, hackable offline speech to text - using the VOSK-API.
TTS - 🐸💬 - a deep learning toolkit for Text-to-Speech, battle-tested in research and production
synonyme - UTF-8 encoded list of German synonyms
flowtron - Flowtron is an auto-regressive flow-based generative network for text to speech synthesis with control over speech variation and style transfer
hifi-gan - HiFi-GAN: Generative Adversarial Networks for Efficient and High Fidelity Speech Synthesis
FairMOT - [IJCV-2021] FairMOT: On the Fairness of Detection and Re-Identification in Multi-Object Tracking
Lip2Speech - A pipeline to read lips and generate speech for the read content, i.e Lip to Speech Synthesis.
mlp-singer - Official implementation of MLP Singer: Towards Rapid Parallel Korean Singing Voice Synthesis (IEEE MLSP 2021)
diffwave - DiffWave is a fast, high-quality neural vocoder and waveform synthesizer.