竞赛资料源码-第十四届中国研究生电子设计竞赛——华为命题-----语音合成.zip

# WaveRNN ##### (Update: Vanilla Tacotron One TTS system just implemented - more coming soon!)  Pytorch implementation of Deepmind's WaveRNN model from [Efficient Neural Audio Synthesis](https://arxiv.org/abs/1802.08435v1) # Installation Ensure you have: * Python >= 3.6 * [Pytorch 1 with CUDA](https://pytorch.org/) Then install the rest with pip: > pip install -r requirements.txt # How to Use ### Quick Start If you want to use TTS functionality immediately you can simply use: > python quick_start.py This will generate everything in the default sentences.txt file and output to a new 'quick_start' folder where you can playback the wav files and take a look at the attention plots You can also use that script to generate custom tts sentences and/or use '-u' to generate unbatched (better audio quality): > python quick_start.py -u --input_text "What will happen if I run this command?' ### Training your own Models  Download the [LJSpeech](https://keithito.com/LJ-Speech-Dataset/) Dataset. Edit **hparams.py**, point **wav_path** to your dataset and run: > python preprocess.py or use preprocess.py --path to point directly to the dataset ___ Here's my recommendation on what order to run things: 1 - Train Tacotron with: > python train_tacotron.py 2 - You can leave that finish training or at any point you can use: > python train_tacotron.py --force_gta this will force tactron to create a GTA dataset even if it hasn't finish training. 3 - Train WaveRNN with: > python train_wavernn.py --gta NB: You can always just run train_wavernn.py without --gta if you're not interested in TTS. 4 - Generate Sentences with both models using: > python gen_tacotron.py this will generate default sentences. If you want generate custom sentences you can use > python gen_tacotron.py --input_text "this is whatever you want it to be" And finally, you can always use --help on any of those scripts to see what options are available :) # Samples [Can be found here.](https://fatchord.github.io/model_outputs/) # Pretrained Models Currently there are two pretrained models available in the /pretrained/ folder': Both are trained on LJSpeech * WaveRNN (Mixture of Logistics output) trained to 800k steps * Tacotron trained to 180k steps ____ ### References * [Efficient Neural Audio Synthesis](https://arxiv.org/abs/1802.08435v1) * [Tacotron: Towards End-to-End Speech Synthesis](https://arxiv.org/abs/1703.10135) * [Natural TTS Synthesis by Conditioning WaveNet on Mel Spectrogram Predictions](https://arxiv.org/abs/1712.05884) ### Acknowlegements * [https://github.com/keithito/tacotron](https://github.com/keithito/tacotron) * [https://github.com/r9y9/wavenet_vocoder](https://github.com/r9y9/wavenet_vocoder) * Special thanks to github users [G-Wang](https://github.com/G-Wang), [geneing](https://github.com/geneing) & [erogol](https://github.com/erogol)