231 lines
5.2 KiB
Markdown
231 lines
5.2 KiB
Markdown
## Install and Use Locally
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### Table of Content
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- [Linux and macOS Install](#linux-and-macos-install)
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- [Docker Install for Windows and macOS](#docker-install)
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- [Usage](#usage)
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- [Web UI](#webui)
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- [CLI](#cli)
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- [Python API](#python-api)
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### Linux and macOS Install
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The repo is developed and tested on `Ubuntu 20.04` and `Python 3.9`.
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```bash
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git clone https://github.com/myshell-ai/MeloTTS.git
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cd MeloTTS
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pip install -e .
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python -m unidic download
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```
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If you encountered issues in macOS install, try the [Docker Install](#docker-install)
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### Docker Install
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To avoid compatibility issues, for Windows users and some macOS users, we suggest to run via Docker. Ensure that [you have Docker installed](https://docs.docker.com/engine/install/).
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**Build Docker**
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This could take a few minutes.
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```bash
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git clone https://github.com/myshell-ai/MeloTTS.git
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cd MeloTTS
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docker build -t melotts .
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```
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**Run Docker**
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```bash
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docker run -it -p 8888:8888 melotts
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```
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If your local machine has GPU, then you can choose to run:
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```bash
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docker run --gpus all -it -p 8888:8888 melotts
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```
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Then open [http://localhost:8888](http://localhost:8888) in your browser to use the app.
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## Usage
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### WebUI
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The WebUI supports muliple languages and voices. First, follow the installation steps. Then, simply run:
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```bash
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melo-ui
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# Or: python melo/app.py
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```
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### CLI
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You may use the MeloTTS CLI to interact with MeloTTS. The CLI may be invoked using either `melotts` or `melo`. Here are some examples:
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**Read English text:**
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```bash
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melo "Text to read" output.wav
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```
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**Specify a language:**
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```bash
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melo "Text to read" output.wav --language EN
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```
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**Specify a speaker:**
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```bash
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melo "Text to read" output.wav --language EN --speaker EN-US
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melo "Text to read" output.wav --language EN --speaker EN-AU
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```
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The available speakers are: `EN-Default`, `EN-US`, `EN-BR`, `EN_INDIA` `EN-AU`.
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**Specify a speed:**
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```bash
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melo "Text to read" output.wav --language EN --speaker EN-US --speed 1.5
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melo "Text to read" output.wav --speed 1.5
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```
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**Use a different language:**
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```bash
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melo "text-to-speech 领域近年来发展迅速" zh.wav -l ZH
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```
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**Load from a file:**
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```bash
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melo file.txt out.wav --file
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```
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The full API documentation may be found using:
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```bash
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melo --help
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```
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### Python API
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#### English with Multiple Accents
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```python
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from melo.api import TTS
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# Speed is adjustable
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speed = 1.0
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# CPU is sufficient for real-time inference.
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# You can set it manually to 'cpu' or 'cuda' or 'cuda:0' or 'mps'
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device = 'auto' # Will automatically use GPU if available
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# English
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text = "Did you ever hear a folk tale about a giant turtle?"
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model = TTS(language='EN', device=device)
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speaker_ids = model.hps.data.spk2id
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# American accent
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output_path = 'en-us.wav'
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model.tts_to_file(text, speaker_ids['EN-US'], output_path, speed=speed)
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# British accent
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output_path = 'en-br.wav'
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model.tts_to_file(text, speaker_ids['EN-BR'], output_path, speed=speed)
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# Indian accent
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output_path = 'en-india.wav'
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model.tts_to_file(text, speaker_ids['EN_INDIA'], output_path, speed=speed)
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# Australian accent
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output_path = 'en-au.wav'
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model.tts_to_file(text, speaker_ids['EN-AU'], output_path, speed=speed)
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# Default accent
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output_path = 'en-default.wav'
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model.tts_to_file(text, speaker_ids['EN-Default'], output_path, speed=speed)
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```
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#### Spanish
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```python
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from melo.api import TTS
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# Speed is adjustable
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speed = 1.0
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# CPU is sufficient for real-time inference.
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# You can also change to cuda:0
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device = 'cpu'
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text = "El resplandor del sol acaricia las olas, pintando el cielo con una paleta deslumbrante."
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model = TTS(language='ES', device=device)
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speaker_ids = model.hps.data.spk2id
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output_path = 'es.wav'
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model.tts_to_file(text, speaker_ids['ES'], output_path, speed=speed)
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```
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#### French
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```python
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from melo.api import TTS
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# Speed is adjustable
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speed = 1.0
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device = 'cpu' # or cuda:0
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text = "La lueur dorée du soleil caresse les vagues, peignant le ciel d'une palette éblouissante."
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model = TTS(language='FR', device=device)
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speaker_ids = model.hps.data.spk2id
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output_path = 'fr.wav'
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model.tts_to_file(text, speaker_ids['FR'], output_path, speed=speed)
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```
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#### Chinese
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```python
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from melo.api import TTS
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# Speed is adjustable
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speed = 1.0
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device = 'cpu' # or cuda:0
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text = "我最近在学习machine learning，希望能够在未来的artificial intelligence领域有所建树。"
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model = TTS(language='ZH', device=device)
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speaker_ids = model.hps.data.spk2id
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output_path = 'zh.wav'
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model.tts_to_file(text, speaker_ids['ZH'], output_path, speed=speed)
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```
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#### Japanese
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```python
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from melo.api import TTS
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# Speed is adjustable
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speed = 1.0
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device = 'cpu' # or cuda:0
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text = "彼は毎朝ジョギングをして体を健康に保っています。"
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model = TTS(language='JP', device=device)
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speaker_ids = model.hps.data.spk2id
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output_path = 'jp.wav'
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model.tts_to_file(text, speaker_ids['JP'], output_path, speed=speed)
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```
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#### Korean
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```python
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from melo.api import TTS
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# Speed is adjustable
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speed = 1.0
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device = 'cpu' # or cuda:0
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text = "안녕하세요! 오늘은 날씨가 정말 좋네요."
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model = TTS(language='KR', device=device)
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speaker_ids = model.hps.data.spk2id
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output_path = 'kr.wav'
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model.tts_to_file(text, speaker_ids['KR'], output_path, speed=speed)
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```
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