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🐸 character instead of \:frog\:
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Josh Meyer
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README.md
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README.md
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# <img src="images/coqui-log-green-TTS.png" height="56"/>
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: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.
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: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.
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🐸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.
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🐸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.
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<!-- []() -->
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[](https://opensource.org/licenses/MPL-2.0)
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@ -44,7 +44,7 @@ Please use our dedicated channels for questions and discussion. Help is much mor
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## 🥇 TTS Performance
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<p align="center"><img src="images/TTS-performance.png" width="800" /></p>
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Underlined "TTS*" and "Judy*" are :frog:TTS models
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Underlined "TTS*" and "Judy*" are 🐸TTS models
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<!-- [Details...](https://github.com/coqui-ai/TTS/wiki/Mean-Opinion-Score-Results) -->
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## Features
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@ -88,18 +88,18 @@ Underlined "TTS*" and "Judy*" are :frog:TTS models
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- WaveRNN: [origin](https://github.com/fatchord/WaveRNN/)
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- WaveGrad: [paper](https://arxiv.org/abs/2009.00713)
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You can also help us implement more models. Some :frog: TTS related work can be found [here](https://github.com/erogol/TTS-papers).
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You can also help us implement more models. Some 🐸TTS related work can be found [here](https://github.com/erogol/TTS-papers).
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## Install TTS
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:frog: TTS is tested on Ubuntu 18.04 with **python >= 3.6, < 3.9**.
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🐸TTS is tested on Ubuntu 18.04 with **python >= 3.6, < 3.9**.
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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.
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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.
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```bash
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pip install TTS
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```
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If you plan to code or train models, clone :frog: TTS and install it locally.
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If you plan to code or train models, clone 🐸TTS and install it locally.
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```bash
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git clone https://github.com/coqui-ai/TTS
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@ -137,11 +137,11 @@ Audio examples: [soundcloud](https://soundcloud.com/user-565970875/pocket-articl
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<img src="images/example_model_output.png?raw=true" alt="example_output" width="400"/>
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## Datasets and Data-Loading
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:frog: TTS provides a generic dataloader easy to use for your custom dataset.
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🐸TTS provides a generic dataloader easy to use for your custom dataset.
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You just need to write a simple function to format the dataset. Check ```datasets/preprocess.py``` to see some examples.
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After that, you need to set ```dataset``` fields in ```config.json```.
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Some of the public datasets that we successfully applied :frog: TTS:
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Some of the public datasets that we successfully applied 🐸TTS:
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- [LJ Speech](https://keithito.com/LJ-Speech-Dataset/)
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- [Nancy](http://www.cstr.ed.ac.uk/projects/blizzard/2011/lessac_blizzard2011/)
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@ -152,9 +152,9 @@ Some of the public datasets that we successfully applied :frog: TTS:
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## Example: Synthesizing Speech on Terminal Using the Released Models.
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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.
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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 :frog: TTS models.
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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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@ -231,7 +231,7 @@ In case of any error or intercepted execution, if there is no checkpoint yet und
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You can also enjoy Tensorboard, if you point Tensorboard argument```--logdir``` to the experiment folder.
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## Contribution guidelines
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Please follow the steps below as you send a PR for :frog:. It helps us to keep things organized.
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Please follow the steps below as you send a PR to 🐸. It helps us to keep things organized.
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1. Create a new branch.
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2. Implement your changes.
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