# Run DiffSpeech ## Quick Start ### Install Dependencies Install dependencies following [readme.md](../readme.md) ### Set Config Path and Experiment Name ```bash export CONFIG_NAME=egs/datasets/audio/lj/ds.yaml export MY_EXP_NAME=ds_exp ``` ### Preprocess and binary dataset Prepare dataset following [prepare_data.md](./prepare_data.md) ### Prepare Vocoder Prepare vocoder following [prepare_vocoder.md](./prepare_vocoder.md) ## Training First, you need a pre-trained FastSpeech2 checkpoint `chckpoints/fs2_exp/model_ckpt_steps_160000.ckpt`. To train a FastSpeech 2 model, run: ```bash CUDA_VISIBLE_DEVICES=0 python tasks/run.py --config egs/datasets/audio/lj/fs2_orig.yaml --exp_name fs2_exp --reset ``` Then, run: ```bash CUDA_VISIBLE_DEVICES=0 python tasks/run.py --config $CONFIG_NAME --exp_name $MY_EXP_NAME --reset ``` You can check the training and validation curves open Tensorboard via: ```bash tensorboard --logdir checkpoints/$MY_EXP_NAME ``` ## Inference (Testing) ```bash CUDA_VISIBLE_DEVICES=0 python tasks/run.py --config $CONFIG_NAME --exp_name $MY_EXP_NAME --infer ``` ## Citation If you find this useful for your research, please use the following. ```bib @article{liu2021diffsinger, title={Diffsinger: Singing voice synthesis via shallow diffusion mechanism}, author={Liu, Jinglin and Li, Chengxi and Ren, Yi and Chen, Feiyang and Liu, Peng and Zhao, Zhou}, journal={arXiv preprint arXiv:2105.02446}, volume={2}, year={2021} } ```