From 32d21545ace69def11b013a5332cad013508b6eb Mon Sep 17 00:00:00 2001 From: =?UTF-8?q?Eren=20G=C3=B6lge?= Date: Fri, 22 Jan 2021 02:30:32 +0100 Subject: [PATCH] README update --- README.md | 21 ++++++++++++++++++++- 1 file changed, 20 insertions(+), 1 deletion(-) diff --git a/README.md b/README.md index 723568e1..0738f2e9 100644 --- a/README.md +++ b/README.md @@ -36,8 +36,10 @@ Please use our dedicated channels for questions and discussion. Help is much mor | Type | Links | | ------------------------------- | --------------------------------------- | | 👩🏾‍🏫 **Tutorials and Examples** | [TTS/Wiki](https://github.com/mozilla/TTS/wiki/TTS-Notebooks-and-Tutorials) | -| 🤖 **Released Models** | [TTS/Wiki](https://github.com/mozilla/TTS/wiki/Released-Models)| +| 🚀 **Released Models** | [TTS/Wiki](https://github.com/mozilla/TTS/wiki/Released-Models)| | 💻 **Docker Image** | [Repository by @synesthesiam](https://github.com/synesthesiam/docker-mozillatts)| +| 🖥️ **Demo Server** | [TTS/server](https://github.com/mozilla/TTS/tree/master/TTS/server)| +| 🤖 **Running TTS on Terminal** | [TTS/README.md](https://github.com/mozilla/TTS#example-synthesizing-speech-on-terminal-using-the-released-models)| ## 🥇 TTS Performance

@@ -137,6 +139,23 @@ Some of the public datasets that we successfully applied TTS: - [LibriTTS](https://openslr.org/60/) - [Spanish](https://drive.google.com/file/d/1Sm_zyBo67XHkiFhcRSQ4YaHPYM0slO_e/view?usp=sharing) - thx! @carlfm01 +## Example: Synthesizing Speech on Terminal Using the Released Models. + +TTS provides a CLI interface for synthesizing speech using pre-trained models. You can either use your own model or the release models under the TTS project. + +Listing released TTS models. +```./TTS/bin/synthesize.py --list_models``` + +Run a tts and a vocoder model from the released model list. (Simply copy and paste the full model names from the list as arguments for the command below.) +```./TTS/bin/synthesize.py --text "Text for TTS" --model_name "///" --vocoder_name "///" --output_path``` + +Run your own TTS model (Using Griffin-Lim Vocoder) +```./TTS/bin/synthesize.py --text "Text for TTS" --model_path path/to/model.pth.tar --config_path path/to/config.json --out_path output/path/speech.wav``` + +Run your own TTS and Vocoder models +```./TTS/bin/synthesize.py --text "Text for TTS" --model_path path/to/config.json --config_path path/to/model.pth.tar --out_path output/path/speech.wav --vocoder_path path/to/vocoder.pth.tar --vocoder_config_path path/to/vocoder_config.json``` + + ## Example: Training and Fine-tuning LJ-Speech Dataset Here you can find a [CoLab](https://gist.github.com/erogol/97516ad65b44dbddb8cd694953187c5b) notebook for a hands-on example, training LJSpeech. Or you can manually follow the guideline below.