mirror of https://github.com/coqui-ai/TTS.git
103 lines
3.5 KiB
Markdown
103 lines
3.5 KiB
Markdown
(synthesizing_speech)=
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# Synthesizing Speech
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First, you need to install TTS. We recommend using PyPi. You need to call the command below:
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```bash
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$ pip install TTS
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```
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After the installation, 2 terminal commands are available.
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1. TTS Command Line Interface (CLI). - `tts`
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2. Local Demo Server. - `tts-server`
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## On the Commandline - `tts`
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After the installation, 🐸TTS provides a CLI interface for synthesizing speech using pre-trained models. You can either use your own model or the release models under 🐸TTS.
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Listing released 🐸TTS models.
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```bash
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tts --list_models
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```
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Run a TTS model, from the release models list, with its default vocoder. (Simply copy and paste the full model names from the list as arguments for the command below.)
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```bash
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tts --text "Text for TTS" \
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--model_name "<type>/<language>/<dataset>/<model_name>" \
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--out_path folder/to/save/output.wav
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```
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Run a tts and a vocoder model from the released model list. Note that not every vocoder is compatible with every TTS model.
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```bash
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tts --text "Text for TTS" \
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--model_name "<type>/<language>/<dataset>/<model_name>" \
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--vocoder_name "<type>/<language>/<dataset>/<model_name>" \
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--out_path folder/to/save/output.wav
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```
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Run your own TTS model (Using Griffin-Lim Vocoder)
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```bash
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tts --text "Text for TTS" \
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--model_path path/to/model.pth \
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--config_path path/to/config.json \
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--out_path folder/to/save/output.wav
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```
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Run your own TTS and Vocoder models
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```bash
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tts --text "Text for TTS" \
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--config_path path/to/config.json \
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--model_path path/to/model.pth \
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--out_path folder/to/save/output.wav \
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--vocoder_path path/to/vocoder.pth \
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--vocoder_config_path path/to/vocoder_config.json
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```
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Run a multi-speaker TTS model from the released models list.
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```bash
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tts --model_name "<type>/<language>/<dataset>/<model_name>" --list_speaker_idxs # list the possible speaker IDs.
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tts --text "Text for TTS." --out_path output/path/speech.wav --model_name "<language>/<dataset>/<model_name>" --speaker_idx "<speaker_id>"
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```
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**Note:** You can use ```./TTS/bin/synthesize.py``` if you prefer running ```tts``` from the TTS project folder.
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## On the Demo Server - `tts-server`
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<!-- <img src="https://raw.githubusercontent.com/coqui-ai/TTS/main/images/demo_server.gif" height="56"/> -->
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You can boot up a demo 🐸TTS server to run an inference with your models. Note that the server is not optimized for performance
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but gives you an easy way to interact with the models.
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The demo server provides pretty much the same interface as the CLI command.
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```bash
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tts-server -h # see the help
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tts-server --list_models # list the available models.
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```
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Run a TTS model, from the release models list, with its default vocoder.
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If the model you choose is a multi-speaker TTS model, you can select different speakers on the Web interface and synthesize
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speech.
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```bash
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tts-server --model_name "<type>/<language>/<dataset>/<model_name>"
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```
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Run a TTS and a vocoder model from the released model list. Note that not every vocoder is compatible with every TTS model.
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```bash
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tts-server --model_name "<type>/<language>/<dataset>/<model_name>" \
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--vocoder_name "<type>/<language>/<dataset>/<model_name>"
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```
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## TorchHub
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You can also use [this simple colab notebook](https://colab.research.google.com/drive/1iAe7ZdxjUIuN6V4ooaCt0fACEGKEn7HW?usp=sharing) using TorchHub to synthesize speech. |