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Michael Hansen
2023-06-12 11:45:06 -05:00
parent 3f5d3b56a8
commit ec25c8b489
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@@ -18,9 +18,7 @@ Voices are trained with [VITS](https://github.com/jaywalnut310/vits/) and export
Our goal is to support Home Assistant and the [Year of Voice](https://www.home-assistant.io/blog/2022/12/20/year-of-voice/).
Download voices from [the release](https://github.com/rhasspy/piper/releases/tag/v0.0.2).
Supported languages:
[Download voices](https://github.com/rhasspy/piper/releases/tag/v0.0.2) for the supported languages:
* Catalan (ca)
* Danish (da)
@@ -50,13 +48,12 @@ Supported languages:
Download a release:
* [amd64](https://github.com/rhasspy/piper/releases/download/v0.0.2/piper_amd64.tar.gz) (desktop Linux)
* [arm64](https://github.com/rhasspy/piper/releases/download/v0.0.2/piper_arm64.tar.gz) (Raspberry Pi 4)
* [amd64](https://github.com/rhasspy/piper/releases/download/v1.0.0/piper_amd64.tar.gz) (desktop Linux)
* [arm64](https://github.com/rhasspy/piper/releases/download/v1.0.0/piper_arm64.tar.gz) (Raspberry Pi 4)
If you want to build from source, see the [Makefile](Makefile) and [C++ source](src/cpp). Piper depends on a patched `espeak-ng` in [lib](lib), which includes a way to get access to the "terminator" used to end each clause/sentence.
The ONNX runtime is expected in `lib/Linux-$(uname -m)`, so `lib/Linux-x86_64`, etc. You can change this path in `src/cpp/CMakeLists.txt` if necessary.
Last tested with [onnxruntime](https://github.com/microsoft/onnxruntime) 1.14.1.
If you want to build from source, see the [Makefile](Makefile) and [C++ source](src/cpp).
You must download and extract [piper-phonemize](https://github.com/rhasspy/piper-phonemize) to `lib/Linux-$(uname -m)/piper_phonemize` before building.
For example, `lib/Linux-x86_64/piper_phonemize/lib/libpiper_phonemize.so` should exist for AMD/Intel machines (as well as everything else from `libpiper_phonemize-amd64.tar.gz`).
## Usage
@@ -125,7 +122,7 @@ python3 -m piper_train.preprocess \
--sample-rate 22050
```
Datasets must either be in the [LJSpeech](https://keithito.com/LJ-Speech-Dataset/) format or from [Mimic Recording Studio](https://github.com/MycroftAI/mimic-recording-studio) (`--dataset-format mycroft`).
Datasets must either be in the [LJSpeech](https://keithito.com/LJ-Speech-Dataset/) format (with only id/text columns or id/speaker/text) or from [Mimic Recording Studio](https://github.com/MycroftAI/mimic-recording-studio) (`--dataset-format mycroft`).
Finally, you can train: