diff --git a/CHANGELOG.md b/CHANGELOG.md index b37fb777b7230ed3dc9bcd921b5fc28065365e94..3178434c4cc9de48f71265ea34797a1dc7639d61 100644 --- a/CHANGELOG.md +++ b/CHANGELOG.md @@ -1,5 +1,10 @@ # Changelog +Date: 2022-1-19, Author: yt605155624. +Add features to: T2S: + - Add csmsc Tacotron2. + - PRLink: https://github.com/PaddlePaddle/PaddleSpeech/pull/1314 + Date: 2022-1-10, Author: Jackwaterveg. Add features to: CLI: diff --git a/examples/csmsc/tts0/README.md b/examples/csmsc/tts0/README.md new file mode 100644 index 0000000000000000000000000000000000000000..3f3b4a3949a2fb9eae8fc71543e740f1a9ad1430 --- /dev/null +++ b/examples/csmsc/tts0/README.md @@ -0,0 +1,250 @@ +# Tacotron2 with CSMSC +This example contains code used to train a [Tacotron2](https://arxiv.org/abs/1712.05884) model with [Chinese Standard Mandarin Speech Copus](https://www.data-baker.com/open_source.html). + +## Dataset +### Download and Extract +Download CSMSC from it's [Official Website](https://test.data-baker.com/data/index/source). + +### Get MFA Result and Extract +We use [MFA](https://github.com/MontrealCorpusTools/Montreal-Forced-Aligner) to get phonemes for Tacotron2, the durations of MFA are not needed here. +You can download from here [baker_alignment_tone.tar.gz](https://paddlespeech.bj.bcebos.com/MFA/BZNSYP/with_tone/baker_alignment_tone.tar.gz), or train your MFA model reference to [mfa example](https://github.com/PaddlePaddle/PaddleSpeech/tree/develop/examples/other/mfa) of our repo. + +## Get Started +Assume the path to the dataset is `~/datasets/BZNSYP`. +Assume the path to the MFA result of CSMSC is `./baker_alignment_tone`. +Run the command below to +1. **source path**. +2. preprocess the dataset. +3. train the model. +4. synthesize wavs. + - synthesize waveform from `metadata.jsonl`. + - synthesize waveform from a text file. + +```bash +./run.sh +``` +You can choose a range of stages you want to run, or set `stage` equal to `stop-stage` to use only one stage, for example, running the following command will only preprocess the dataset. +```bash +./run.sh --stage 0 --stop-stage 0 +``` +### Data Preprocessing +```bash +./local/preprocess.sh ${conf_path} +``` +When it is done. A `dump` folder is created in the current directory. The structure of the dump folder is listed below. + +```text +dump +├── dev +│ ├── norm +│ └── raw +├── phone_id_map.txt +├── speaker_id_map.txt +├── test +│ ├── norm +│ └── raw +└── train + ├── energy_stats.npy + ├── norm + ├── pitch_stats.npy + ├── raw + └── speech_stats.npy +``` +The dataset is split into 3 parts, namely `train`, `dev`, and` test`, each of which contains a `norm` and `raw` subfolder. The raw folder contains speech、pitch and energy features of each utterance, while the norm folder contains normalized ones. The statistics used to normalize features are computed from the training set, which is located in `dump/train/*_stats.npy`. + +Also, there is a `metadata.jsonl` in each subfolder. It is a table-like file that contains phones, text_lengths, speech_lengths, durations, the path of speech features, the path of pitch features, the path of energy features, speaker, and the id of each utterance. + +### Model Training +```bash +CUDA_VISIBLE_DEVICES=${gpus} ./local/train.sh ${conf_path} ${train_output_path} +``` +`./local/train.sh` calls `${BIN_DIR}/train.py`. +Here's the complete help message. +```text +usage: train.py [-h] [--config CONFIG] [--train-metadata TRAIN_METADATA] + [--dev-metadata DEV_METADATA] [--output-dir OUTPUT_DIR] + [--ngpu NGPU] [--phones-dict PHONES_DICT] + +Train a Tacotron2 model. + +optional arguments: + -h, --help show this help message and exit + --config CONFIG tacotron2 config file. + --train-metadata TRAIN_METADATA + training data. + --dev-metadata DEV_METADATA + dev data. + --output-dir OUTPUT_DIR + output dir. + --ngpu NGPU if ngpu == 0, use cpu. + --phones-dict PHONES_DICT + phone vocabulary file. +``` +1. `--config` is a config file in yaml format to overwrite the default config, which can be found at `conf/default.yaml`. +2. `--train-metadata` and `--dev-metadata` should be the metadata file in the normalized subfolder of `train` and `dev` in the `dump` folder. +3. `--output-dir` is the directory to save the results of the experiment. Checkpoints are saved in `checkpoints/` inside this directory. +4. `--ngpu` is the number of gpus to use, if ngpu == 0, use cpu. +5. `--phones-dict` is the path of the phone vocabulary file. + +### Synthesizing +We use [parallel wavegan](https://github.com/PaddlePaddle/PaddleSpeech/tree/develop/examples/csmsc/voc1) as the neural vocoder. +Download pretrained parallel wavegan model from [pwg_baker_ckpt_0.4.zip](https://paddlespeech.bj.bcebos.com/Parakeet/released_models/pwgan/pwg_baker_ckpt_0.4.zip) and unzip it. +```bash +unzip pwg_baker_ckpt_0.4.zip +``` +Parallel WaveGAN checkpoint contains files listed below. +```text +pwg_baker_ckpt_0.4 +├── pwg_default.yaml # default config used to train parallel wavegan +├── pwg_snapshot_iter_400000.pdz # model parameters of parallel wavegan +└── pwg_stats.npy # statistics used to normalize spectrogram when training parallel wavegan +``` +`./local/synthesize.sh` calls `${BIN_DIR}/../synthesize.py`, which can synthesize waveform from `metadata.jsonl`. +```bash +CUDA_VISIBLE_DEVICES=${gpus} ./local/synthesize.sh ${conf_path} ${train_output_path} ${ckpt_name} +``` +```text +usage: synthesize.py [-h] + [--am {speedyspeech_csmsc,fastspeech2_csmsc,fastspeech2_ljspeech,fastspeech2_aishell3,fastspeech2_vctk,tacotron2_csmsc}] + [--am_config AM_CONFIG] [--am_ckpt AM_CKPT] + [--am_stat AM_STAT] [--phones_dict PHONES_DICT] + [--tones_dict TONES_DICT] [--speaker_dict SPEAKER_DICT] + [--voice-cloning VOICE_CLONING] + [--voc {pwgan_csmsc,pwgan_ljspeech,pwgan_aishell3,pwgan_vctk,mb_melgan_csmsc}] + [--voc_config VOC_CONFIG] [--voc_ckpt VOC_CKPT] + [--voc_stat VOC_STAT] [--ngpu NGPU] + [--test_metadata TEST_METADATA] [--output_dir OUTPUT_DIR] + +Synthesize with acoustic model & vocoder + +optional arguments: + -h, --help show this help message and exit + --am {speedyspeech_csmsc,fastspeech2_csmsc,fastspeech2_ljspeech,fastspeech2_aishell3,fastspeech2_vctk,tacotron2_csmsc} + Choose acoustic model type of tts task. + --am_config AM_CONFIG + Config of acoustic model. Use deault config when it is + None. + --am_ckpt AM_CKPT Checkpoint file of acoustic model. + --am_stat AM_STAT mean and standard deviation used to normalize + spectrogram when training acoustic model. + --phones_dict PHONES_DICT + phone vocabulary file. + --tones_dict TONES_DICT + tone vocabulary file. + --speaker_dict SPEAKER_DICT + speaker id map file. + --voice-cloning VOICE_CLONING + whether training voice cloning model. + --voc {pwgan_csmsc,pwgan_ljspeech,pwgan_aishell3,pwgan_vctk,mb_melgan_csmsc} + Choose vocoder type of tts task. + --voc_config VOC_CONFIG + Config of voc. Use deault config when it is None. + --voc_ckpt VOC_CKPT Checkpoint file of voc. + --voc_stat VOC_STAT mean and standard deviation used to normalize + spectrogram when training voc. + --ngpu NGPU if ngpu == 0, use cpu. + --test_metadata TEST_METADATA + test metadata. + --output_dir OUTPUT_DIR + output dir. +``` +`./local/synthesize_e2e.sh` calls `${BIN_DIR}/../synthesize_e2e.py`, which can synthesize waveform from text file. +```bash +CUDA_VISIBLE_DEVICES=${gpus} ./local/synthesize_e2e.sh ${conf_path} ${train_output_path} ${ckpt_name} +``` +```text +usage: synthesize_e2e.py [-h] + [--am {speedyspeech_csmsc,speedyspeech_aishell3,fastspeech2_csmsc,fastspeech2_ljspeech,fastspeech2_aishell3,fastspeech2_vctk,tacotron2_csmsc}] + [--am_config AM_CONFIG] [--am_ckpt AM_CKPT] + [--am_stat AM_STAT] [--phones_dict PHONES_DICT] + [--tones_dict TONES_DICT] + [--speaker_dict SPEAKER_DICT] [--spk_id SPK_ID] + [--voc {pwgan_csmsc,pwgan_ljspeech,pwgan_aishell3,pwgan_vctk,mb_melgan_csmsc,style_melgan_csmsc,hifigan_csmsc}] + [--voc_config VOC_CONFIG] [--voc_ckpt VOC_CKPT] + [--voc_stat VOC_STAT] [--lang LANG] + [--inference_dir INFERENCE_DIR] [--ngpu NGPU] + [--text TEXT] [--output_dir OUTPUT_DIR] + +Synthesize with acoustic model & vocoder + +optional arguments: + -h, --help show this help message and exit + --am {speedyspeech_csmsc,speedyspeech_aishell3,fastspeech2_csmsc,fastspeech2_ljspeech,fastspeech2_aishell3,fastspeech2_vctk,tacotron2_csmsc} + Choose acoustic model type of tts task. + --am_config AM_CONFIG + Config of acoustic model. Use deault config when it is + None. + --am_ckpt AM_CKPT Checkpoint file of acoustic model. + --am_stat AM_STAT mean and standard deviation used to normalize + spectrogram when training acoustic model. + --phones_dict PHONES_DICT + phone vocabulary file. + --tones_dict TONES_DICT + tone vocabulary file. + --speaker_dict SPEAKER_DICT + speaker id map file. + --spk_id SPK_ID spk id for multi speaker acoustic model + --voc {pwgan_csmsc,pwgan_ljspeech,pwgan_aishell3,pwgan_vctk,mb_melgan_csmsc,style_melgan_csmsc,hifigan_csmsc} + Choose vocoder type of tts task. + --voc_config VOC_CONFIG + Config of voc. Use deault config when it is None. + --voc_ckpt VOC_CKPT Checkpoint file of voc. + --voc_stat VOC_STAT mean and standard deviation used to normalize + spectrogram when training voc. + --lang LANG Choose model language. zh or en + --inference_dir INFERENCE_DIR + dir to save inference models + --ngpu NGPU if ngpu == 0, use cpu. + --text TEXT text to synthesize, a 'utt_id sentence' pair per line. + --output_dir OUTPUT_DIR + output dir. +``` +1. `--am` is acoustic model type with the format {model_name}_{dataset} +2. `--am_config`, `--am_checkpoint`, `--am_stat` and `--phones_dict` are arguments for acoustic model, which correspond to the 4 files in the Tacotron2 pretrained model. +3. `--voc` is vocoder type with the format {model_name}_{dataset} +4. `--voc_config`, `--voc_checkpoint`, `--voc_stat` are arguments for vocoder, which correspond to the 3 files in the parallel wavegan pretrained model. +5. `--lang` is the model language, which can be `zh` or `en`. +6. `--test_metadata` should be the metadata file in the normalized subfolder of `test` in the `dump` folder. +7. `--text` is the text file, which contains sentences to synthesize. +8. `--output_dir` is the directory to save synthesized audio files. +9. `--ngpu` is the number of gpus to use, if ngpu == 0, use cpu. + + +## Pretrained Model +Pretrained Tacotron2 model with no silence in the edge of audios: +- [tacotron2_csmsc_ckpt_0.2.0.zip](https://paddlespeech.bj.bcebos.com/Parakeet/released_models/tacotron2/tacotron2_csmsc_ckpt_0.2.0.zip) + + +Model | Step | eval/loss | eval/l1_loss | eval/mse_loss | eval/bce_loss| eval/attn_loss +:-------------:| :------------:| :-----: | :-----: | :--------: |:--------:|:---------: +default| 1(gpu) x 30600|0.57185|0.39614|0.14642|0.029|5.8e-05| + +Tacotron2 checkpoint contains files listed below. +```text +tacotron2_csmsc_ckpt_0.2.0 +├── default.yaml # default config used to train Tacotron2 +├── phone_id_map.txt # phone vocabulary file when training Tacotron2 +├── snapshot_iter_30600.pdz # model parameters and optimizer states +└── speech_stats.npy # statistics used to normalize spectrogram when training Tacotron2 +``` +You can use the following scripts to synthesize for `${BIN_DIR}/../sentences.txt` using pretrained Tacotron2 and parallel wavegan models. +```bash +source path.sh + +FLAGS_allocator_strategy=naive_best_fit \ +FLAGS_fraction_of_gpu_memory_to_use=0.01 \ +python3 ${BIN_DIR}/../synthesize_e2e.py \ + --am=tacotron2_csmsc \ + --am_config=tacotron2_csmsc_ckpt_0.2.0/default.yaml \ + --am_ckpt=tacotron2_csmsc_ckpt_0.2.0/snapshot_iter_30600.pdz \ + --am_stat=tacotron2_csmsc_ckpt_0.2.0/speech_stats.npy \ + --voc=pwgan_csmsc \ + --voc_config=pwg_baker_ckpt_0.4/pwg_default.yaml \ + --voc_ckpt=pwg_baker_ckpt_0.4/pwg_snapshot_iter_400000.pdz \ + --voc_stat=pwg_baker_ckpt_0.4/pwg_stats.npy \ + --lang=zh \ + --text=${BIN_DIR}/../sentences.txt \ + --output_dir=exp/default/test_e2e \ + --inference_dir=exp/default/inference \ + --phones_dict=tacotron2_csmsc_ckpt_0.2.0/phone_id_map.txt +``` diff --git a/examples/csmsc/tts3/run.sh b/examples/csmsc/tts3/run.sh index 8f06e933cccfd77113c4b72956f28ff74aec2037..5c394c9f9003bc8f0c1d95624605074f9b807001 100755 --- a/examples/csmsc/tts3/run.sh +++ b/examples/csmsc/tts3/run.sh @@ -36,7 +36,3 @@ if [ ${stage} -le 3 ] && [ ${stop_stage} -ge 3 ]; then CUDA_VISIBLE_DEVICES=${gpus} ./local/synthesize_e2e.sh ${conf_path} ${train_output_path} ${ckpt_name} || exit -1 fi -if [ ${stage} -le 4 ] && [ ${stop_stage} -ge 4 ]; then - # inference with static model - CUDA_VISIBLE_DEVICES=${gpus} ./local/inference.sh ${train_output_path} || exit -1 -fi diff --git a/examples/other/1xt2x/src_deepspeech2x/models/ds2/deepspeech2.py b/examples/other/1xt2x/src_deepspeech2x/models/ds2/deepspeech2.py index 59be4222202b1cd2e7a51e18a92583ec7caed3e6..f6e185ff1dd8f461635c1c64c941893aed4984d3 100644 --- a/examples/other/1xt2x/src_deepspeech2x/models/ds2/deepspeech2.py +++ b/examples/other/1xt2x/src_deepspeech2x/models/ds2/deepspeech2.py @@ -169,7 +169,7 @@ class DeepSpeech2Model(nn.Layer): eouts, eouts_len = self.encoder(audio, audio_len) probs = self.decoder.softmax(eouts) batch_size = probs.shape[0] - self.decoder.reset_decoder(batch_size = batch_size) + self.decoder.reset_decoder(batch_size=batch_size) self.decoder.next(probs, eouts_len) trans_best, trans_beam = self.decoder.decode() return trans_best diff --git a/paddleaudio/CHANGELOG.md b/paddleaudio/CHANGELOG.md index 4dc68c6ff8e4ba0e0e4e14d5025b38d958d9c3b0..825c32f0d03d98995ebe3e6d797f14daf2df51d9 100644 --- a/paddleaudio/CHANGELOG.md +++ b/paddleaudio/CHANGELOG.md @@ -1,2 +1 @@ # Changelog - diff --git a/paddlespeech/cli/st/infer.py b/paddlespeech/cli/st/infer.py index 1276424c509c961cc8d4555a59076758e1f76e78..cb97350210afdbe12a0e861238140278dbeb63a0 100644 --- a/paddlespeech/cli/st/infer.py +++ b/paddlespeech/cli/st/infer.py @@ -173,8 +173,8 @@ class STExecutor(BaseExecutor): self.config.decode.decoding_method = "fullsentence" with UpdateConfig(self.config): - self.config.cmvn_path = os.path.join( - res_path, self.config.cmvn_path) + self.config.cmvn_path = os.path.join(res_path, + self.config.cmvn_path) self.config.spm_model_prefix = os.path.join( res_path, self.config.spm_model_prefix) self.text_feature = TextFeaturizer( diff --git a/paddlespeech/cli/utils.py b/paddlespeech/cli/utils.py index 63b670c863111719c3158d82dc4517bf0dc29d6a..d11178df8e6ecf24040ceb9df43be2576fa91920 100644 --- a/paddlespeech/cli/utils.py +++ b/paddlespeech/cli/utils.py @@ -24,11 +24,11 @@ from typing import Any from typing import Dict import paddle -import paddleaudio import requests import yaml from paddle.framework import load +import paddleaudio from . import download from .. import __version__ from .entry import commands