Replies: 8 comments 11 replies
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Thx ! We also plan to expand 🐸 TTS's use in offline and low-compute devices. Currently, some models we release are already real-time using simply the torch back-end. Targeting the mobile, we can make use of Torch Script, ONNX or TF-Lite export. So one step at a time we plan to get there. Actually you can already run the vanilla Tacotron on TF-Lite. A bit of documentation is here https://github.com/coqui-ai/TTS/wiki/Converting-Torch-Tacotron-to-TF-2.0 |
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There are currently 3 FOSS TTSEs for Mobile https://search.f-droid.org/?q=tts+engine&lang=en |
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Any update on this? Just discovered this project and I am amazed this does not exist yet on Android... |
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I'm curious, why do so many TTS projects not bundle for Android? It seems strange, especially when TTS is most used on mobile devices |
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Note that currently Coqui is less reliable, and orders of magnitude slower than Android TTS options. |
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Just a bump for mobile support. I run an open source project that provides speech output tools for people with disabilities, and in the last year there have been multiple Android devices that are losing their native TTS options. We have many international users, and right now I have to pay a healthy chunk for a proprietary offline TTS provider in order to ensure support for everyone. I'd love to start routing some of that investment to something more open that can benefit more people. Open source offline as flexible and modern as Coqui would have a huge impact on the disability community. |
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Please see You can use sherpa-onnx to run VITS models from Coqui on Android and also embedded devices, e.g., raspberry pi. We have pre-built Android APKs for the VITS English models from Coqui. |
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I'm trying to understand how this project works, specially whether it's entirely offline or not. Well, which one is it? Do my text go through a online server before they're speaking? |
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This repository is really great! Decent samples too.
I see a huge opportunity for this to be extended to support mobile.
There are a number of obstacles to this of course, including running on TF-Lite.
If you ported it to Dart you could transpile it to iOS and Android.
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