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144 lines
5.0 KiB
Markdown
144 lines
5.0 KiB
Markdown
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A fast, local neural text to speech system that sounds great and is optimized for the Raspberry Pi 4.
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Piper is used in a [variety of projects](#people-using-piper).
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``` sh
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echo 'Welcome to the world of speech synthesis!' | \
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./piper --model en-us-blizzard_lessac-medium.onnx --output_file welcome.wav
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```
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[Listen to voice samples](https://rhasspy.github.io/piper-samples) and check out a [video tutorial by Thorsten Müller](https://youtu.be/rjq5eZoWWSo)
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[](https://nabucasa.com)
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Voices are trained with [VITS](https://github.com/jaywalnut310/vits/) and exported to the [onnxruntime](https://onnxruntime.ai/).
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## Voices
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Our goal is to support Home Assistant and the [Year of Voice](https://www.home-assistant.io/blog/2022/12/20/year-of-voice/).
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[Download voices](https://huggingface.co/rhasspy/piper-voices/tree/main) for the supported languages:
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* Catalan (ca_ES)
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* Danish (da_DK)
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* German (de_DE)
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* English (en_GB, en_US)
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* Spanish (es_ES, es_MX)
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* Finnish (fi_FI)
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* French (fr_FR)
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* Greek (el_GR)
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* Icelandic (is_IS)
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* Italian (it_IT)
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* Georgian (ka_GE)
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* Kazakh (kk_KZ)
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* Nepali (ne_NP)
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* Dutch (nl_BE, nl_NL)
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* Norwegian (no_NO)
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* Polish (pl_PL)
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* Portuguese (pt_BR)
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* Russian (ru_RU)
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* Swedish (sv_SE)
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* Swahili (sw_CD)
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* Ukrainian (uk_UA)
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* Vietnamese (vi_VN)
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* Chinese (zh_CN)
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## Installation
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Download a release:
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* [amd64](https://github.com/rhasspy/piper/releases/download/v1.0.0/piper_amd64.tar.gz) (64-bit desktop Linux)
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* [arm64](https://github.com/rhasspy/piper/releases/download/v1.0.0/piper_arm64.tar.gz) (64-bit Raspberry Pi 4)
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* [armv7](https://github.com/rhasspy/piper/releases/download/v1.0.0/piper_armv7.tar.gz) (32-bit Raspberry Pi 3/4)
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If you want to build from source, see the [Makefile](Makefile) and [C++ source](src/cpp).
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You must download and extract [piper-phonemize](https://github.com/rhasspy/piper-phonemize) to `lib/Linux-$(uname -m)/piper_phonemize` before building.
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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`).
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## Usage
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1. [Download a voice](#voices) and extract the `.onnx` and `.onnx.json` files
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2. Run the `piper` binary with text on standard input, `--model /path/to/your-voice.onnx`, and `--output_file output.wav`
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For example:
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``` sh
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echo 'Welcome to the world of speech synthesis!' | \
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./piper --model en-us-lessac-medium.onnx --output_file welcome.wav
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```
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For multi-speaker models, use `--speaker <number>` to change speakers (default: 0).
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See `piper --help` for more options.
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### JSON Input
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The `piper` executable can accept JSON input when using the `--json-input` flag. Each line of input must be a JSON object with `text` field. For example:
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``` json
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{ "text": "First sentence to speak." }
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{ "text": "Second sentence to speak." }
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```
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Optional fields include:
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* `speaker` - string
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* Name of the speaker to use from `speaker_id_map` in config (multi-speaker voices only)
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* `speaker_id` - number
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* Id of speaker to use from 0 to number of speakers - 1 (multi-speaker voices only, overrides "speaker")
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* `output_file` - string
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* Path to output WAV file
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The following example writes two sentences with different speakers to different files:
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``` json
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{ "text": "First speaker.", "speaker_id": 0, "output_file": "/tmp/speaker_0.wav" }
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{ "text": "Second speaker.", "speaker_id": 1, "output_file": "/tmp/speaker_1.wav" }
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```
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## People using Piper
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Piper has been used in the following projects/papers:
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* [Home Assistant](https://github.com/home-assistant/addons/blob/master/piper/README.md)
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* [Rhasspy 3](https://github.com/rhasspy/rhasspy3/)
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* [NVDA - NonVisual Desktop Access](https://www.nvaccess.org/post/in-process-8th-may-2023/#voices)
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* [Image Captioning for the Visually Impaired and Blind: A Recipe for Low-Resource Languages](https://www.techrxiv.org/articles/preprint/Image_Captioning_for_the_Visually_Impaired_and_Blind_A_Recipe_for_Low-Resource_Languages/22133894)
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* [Open Voice Operating System](https://github.com/OpenVoiceOS/ovos-tts-plugin-piper)
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* [JetsonGPT](https://github.com/shahizat/jetsonGPT)
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## Training
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See the [training guide](TRAINING.md) and the [source code](src/python).
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Pretrained checkpoints are available on [Hugging Face](https://huggingface.co/datasets/rhasspy/piper-checkpoints/tree/main)
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## Running in Python
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See [src/python_run](src/python_run)
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Run `scripts/setup.sh` to create a virtual environment and install the requirements. Then run:
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``` sh
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echo 'Welcome to the world of speech synthesis!' | scripts/piper \
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--model /path/to/voice.onnx \
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--output_file welcome.wav
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```
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If you'd like to use a GPU, install the `onnxruntime-gpu` package:
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``` sh
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.venv/bin/pip3 install onnxruntime-gpu
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```
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and then run `scripts/piper` with the `--cuda` argument. You will need to have a functioning CUDA environment, such as what's available in [NVIDIA's PyTorch containers](https://catalog.ngc.nvidia.com/orgs/nvidia/containers/pytorch).
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