From 0914c953981478e7ba6aec6992c62fd28ff986cc Mon Sep 17 00:00:00 2001 From: =?UTF-8?q?Eren=20G=C3=B6lge?= Date: Sun, 7 Mar 2021 04:01:11 +0100 Subject: [PATCH] Update README.md frog is here --- README.md | 20 ++++++++++---------- 1 file changed, 10 insertions(+), 10 deletions(-) diff --git a/README.md b/README.md index 64f795ee..c83c8f57 100644 --- a/README.md +++ b/README.md @@ -1,7 +1,7 @@ # -TTS is a library for advanced Text-to-Speech generation. It's built on the latest research, was designed to achieve the best trade-off among ease-of-training, speed and quality. -TTS comes with [pretrained models](https://github.com/coqui-ai/TTS/wiki/Released-Models), tools for measuring dataset quality and already used in **20+ languages** for products and research projects. +:frog: TTS is a library for advanced Text-to-Speech generation. It's built on the latest research, was designed to achieve the best trade-off among ease-of-training, speed and quality. +:frog: TTS comes with [pretrained models](https://github.com/coqui-ai/TTS/wiki/Released-Models), tools for measuring dataset quality and already used in **20+ languages** for products and research projects. [![License]()](https://opensource.org/licenses/MPL-2.0) @@ -88,18 +88,18 @@ Underlined "TTS*" and "Judy*" are :frog:TTS models - WaveRNN: [origin](https://github.com/fatchord/WaveRNN/) - WaveGrad: [paper](https://arxiv.org/abs/2009.00713) -You can also help us implement more models. Some TTS related work can be found [here](https://github.com/erogol/TTS-papers). +You can also help us implement more models. Some :frog: TTS related work can be found [here](https://github.com/erogol/TTS-papers). ## Install TTS -TTS is tested on Ubuntu 18.04 with **python >= 3.6, < 3.9**. +:frog: TTS is tested on Ubuntu 18.04 with **python >= 3.6, < 3.9**. -If you are only interested in [synthesizing speech](https://github.com/coqui-ai/TTS/tree/dev#example-synthesizing-speech-on-terminal-using-the-released-models) with the released TTS models, installing from PyPI is the easiest option. +If you are only interested in [synthesizing speech](https://github.com/coqui-ai/TTS/tree/dev#example-synthesizing-speech-on-terminal-using-the-released-models) with the released :frog: TTS models, installing from PyPI is the easiest option. ```bash pip install TTS ``` -If you plan to code or train models, clone TTS and install it locally. +If you plan to code or train models, clone :frog: TTS and install it locally. ```bash git clone https://github.com/coqui-ai/TTS @@ -137,11 +137,11 @@ Audio examples: [soundcloud](https://soundcloud.com/user-565970875/pocket-articl example_output ## Datasets and Data-Loading -TTS provides a generic dataloader easy to use for your custom dataset. +:frog: TTS provides a generic dataloader easy to use for your custom dataset. You just need to write a simple function to format the dataset. Check ```datasets/preprocess.py``` to see some examples. After that, you need to set ```dataset``` fields in ```config.json```. -Some of the public datasets that we successfully applied TTS: +Some of the public datasets that we successfully applied :frog: TTS: - [LJ Speech](https://keithito.com/LJ-Speech-Dataset/) - [Nancy](http://www.cstr.ed.ac.uk/projects/blizzard/2011/lessac_blizzard2011/) @@ -152,9 +152,9 @@ Some of the public datasets that we successfully applied TTS: ## Example: Synthesizing Speech on Terminal Using the Released Models. -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 the TTS project. +After the installation, :frog: TTS provides a CLI interface for synthesizing speech using pre-trained models. You can either use your own model or the release models under :frog: TTS. -Listing released TTS models. +Listing released :frog: TTS models. ```bash tts --list_models ```