[tts]Update mb melgan (#1272)

* update mb melgan

* update mb melgan, test=tts

docs/source/released_model.md

@@ -49,7 +49,7 @@ Parallel WaveGAN| CSMSC |[PWGAN-csmsc](https://github.com/PaddlePaddle/PaddleSpe
 Parallel WaveGAN| LJSpeech |[PWGAN-ljspeech](https://github.com/PaddlePaddle/PaddleSpeech/tree/develop/examples/ljspeech/voc1)|[pwg_ljspeech_ckpt_0.5.zip](https://paddlespeech.bj.bcebos.com/Parakeet/released_models/pwgan/pwg_ljspeech_ckpt_0.5.zip)|||
 Parallel WaveGAN|AISHELL-3 |[PWGAN-aishell3](https://github.com/PaddlePaddle/PaddleSpeech/tree/develop/examples/aishell3/voc1)|[pwg_aishell3_ckpt_0.5.zip](https://paddlespeech.bj.bcebos.com/Parakeet/released_models/pwgan/pwg_aishell3_ckpt_0.5.zip)|||
 Parallel WaveGAN| VCTK |[PWGAN-vctk](https://github.com/PaddlePaddle/PaddleSpeech/tree/develop/examples/vctk/voc1)|[pwg_vctk_ckpt_0.5.zip](https://paddlespeech.bj.bcebos.com/Parakeet/released_models/pwgan/pwg_vctk_ckpt_0.5.zip)|||
-|Multi Band MelGAN | CSMSC |[MB MelGAN-csmsc](https://github.com/PaddlePaddle/PaddleSpeech/tree/develop/examples/csmsc/voc3) | [mb_melgan_baker_ckpt_0.5.zip](https://paddlespeech.bj.bcebos.com/Parakeet/released_models/mb_melgan/mb_melgan_baker_ckpt_0.5.zip) <br>[mb_melgan_baker_finetune_ckpt_0.5.zip](https://paddlespeech.bj.bcebos.com/Parakeet/released_models/mb_melgan/mb_melgan_baker_finetune_ckpt_0.5.zip)|[mb_melgan_baker_static_0.5.zip](https://paddlespeech.bj.bcebos.com/Parakeet/released_models/mb_melgan/mb_melgan_baker_static_0.5.zip) |8.2MB|
+|Multi Band MelGAN | CSMSC |[MB MelGAN-csmsc](https://github.com/PaddlePaddle/PaddleSpeech/tree/develop/examples/csmsc/voc3) | [mb_melgan_csmsc_ckpt_0.1.1.zip](https://paddlespeech.bj.bcebos.com/Parakeet/released_models/mb_melgan/mb_melgan_csmsc_ckpt_0.1.1.zip) <br>[mb_melgan_baker_finetune_ckpt_0.5.zip](https://paddlespeech.bj.bcebos.com/Parakeet/released_models/mb_melgan/mb_melgan_baker_finetune_ckpt_0.5.zip)|[mb_melgan_csmsc_static_0.1.1.zip](https://paddlespeech.bj.bcebos.com/Parakeet/released_models/mb_melgan/mb_melgan_csmsc_static_0.1.1.zip) |8.2MB|
 Style MelGAN | CSMSC |[Style MelGAN-csmsc](https://github.com/PaddlePaddle/PaddleSpeech/tree/develop/examples/csmsc/voc4)|[style_melgan_csmsc_ckpt_0.1.1.zip](https://paddlespeech.bj.bcebos.com/Parakeet/released_models/style_melgan/style_melgan_csmsc_ckpt_0.1.1.zip)| | |
 HiFiGAN | CSMSC |[HiFiGAN-csmsc](https://github.com/PaddlePaddle/PaddleSpeech/tree/develop/examples/csmsc/voc5)|[hifigan_csmsc_ckpt_0.1.1.zip](https://paddlespeech.bj.bcebos.com/Parakeet/released_models/hifigan/hifigan_csmsc_ckpt_0.1.1.zip)|[hifigan_csmsc_static_0.1.1.zip](https://paddlespeech.bj.bcebos.com/Parakeet/released_models/hifigan/hifigan_csmsc_static_0.1.1.zip)|50MB|
 

examples/csmsc/tts2/local/synthesize_e2e.sh

@@ -38,9 +38,9 @@ if [ ${stage} -le 1 ] && [ ${stop_stage} -ge 1 ]; then
         --am_ckpt=${train_output_path}/checkpoints/${ckpt_name} \
         --am_stat=dump/train/feats_stats.npy \
         --voc=mb_melgan_csmsc \
-        --voc_config=mb_melgan_baker_finetune_ckpt_0.5/finetune.yaml \
-        --voc_ckpt=mb_melgan_baker_finetune_ckpt_0.5/snapshot_iter_2000000.pdz\
-        --voc_stat=mb_melgan_baker_finetune_ckpt_0.5/feats_stats.npy \
+        --voc_config=mb_melgan_csmsc_ckpt_0.1.1/default.yaml \
+        --voc_ckpt=mb_melgan_csmsc_ckpt_0.1.1/snapshot_iter_1000000.pdz\
+        --voc_stat=mb_melgan_csmsc_ckpt_0.1.1/feats_stats.npy \
         --lang=zh \
         --text=${BIN_DIR}/../sentences.txt \
         --output_dir=${train_output_path}/test_e2e \

examples/csmsc/tts3/local/synthesize_e2e.sh

@@ -37,9 +37,9 @@ if [ ${stage} -le 1 ] && [ ${stop_stage} -ge 1 ]; then
         --am_ckpt=${train_output_path}/checkpoints/${ckpt_name} \
         --am_stat=dump/train/speech_stats.npy \
         --voc=mb_melgan_csmsc \
-        --voc_config=mb_melgan_baker_finetune_ckpt_0.5/finetune.yaml \
-        --voc_ckpt=mb_melgan_baker_finetune_ckpt_0.5/snapshot_iter_2000000.pdz\
-        --voc_stat=mb_melgan_baker_finetune_ckpt_0.5/feats_stats.npy \
+        --voc_config=mb_melgan_csmsc_ckpt_0.1.1/default.yaml \
+        --voc_ckpt=mb_melgan_csmsc_ckpt_0.1.1/snapshot_iter_1000000.pdz\
+        --voc_stat=mb_melgan_csmsc_ckpt_0.1.1/feats_stats.npy \
         --lang=zh \
         --text=${BIN_DIR}/../sentences.txt \
         --output_dir=${train_output_path}/test_e2e \

examples/csmsc/voc3/README.md

@@ -152,22 +152,22 @@ TODO:
 The hyperparameter of `finetune.yaml` is not good enough, a smaller `learning_rate` should be used (more `milestones` should be set).
 
 ## Pretrained Models
-The pretrained model can be downloaded here [mb_melgan_baker_ckpt_0.5.zip](https://paddlespeech.bj.bcebos.com/Parakeet/released_models/mb_melgan/mb_melgan_baker_ckpt_0.5.zip).
+The pretrained model can be downloaded here [mb_melgan_csmsc_ckpt_0.1.1.zip](https://paddlespeech.bj.bcebos.com/Parakeet/released_models/mb_melgan/mb_melgan_csmsc_ckpt_0.1.1.zip).
 
 The finetuned model can be downloaded here [mb_melgan_baker_finetune_ckpt_0.5.zip](https://paddlespeech.bj.bcebos.com/Parakeet/released_models/mb_melgan/mb_melgan_baker_finetune_ckpt_0.5.zip).
 
-The static model can be downloaded here [mb_melgan_baker_static_0.5.zip](https://paddlespeech.bj.bcebos.com/Parakeet/released_models/mb_melgan/mb_melgan_baker_static_0.5.zip)
+The static model can be downloaded here [mb_melgan_csmsc_static_0.1.1.zip](https://paddlespeech.bj.bcebos.com/Parakeet/released_models/mb_melgan/mb_melgan_csmsc_static_0.1.1.zip)
 
 Model | Step | eval/generator_loss | eval/log_stft_magnitude_loss|eval/spectral_convergence_loss |eval/sub_log_stft_magnitude_loss|eval/sub_spectral_convergence_loss
 :-------------:| :------------:| :-----: | :-----: | :--------:| :--------:| :--------:
-default| 1(gpu) x 1000000| ——|—— |—— |—— | ——|
+default| 1(gpu) x 1000000| 2.4851|0.71778 |0.2761 |0.66334 |0.2777|
 finetune| 1(gpu) x 1000000|3.196967|0.977804| 0.778484| 0.889576 |0.776756 |
 
 
 Multi Band MelGAN checkpoint contains files listed below.
 
 ```text
-mb_melgan_baker_ckpt_0.5
+mb_melgan_csmsc_ckpt_0.1.1
 ├── default.yaml                  # default config used to train multi band melgan
 ├── feats_stats.npy               # statistics used to normalize spectrogram when training multi band melgan
 └── snapshot_iter_1000000.pdz     # generator parameters of multi band melgan

paddlespeech/cli/asr/infer.py

@@ -211,7 +211,6 @@ class ASRExecutor(BaseExecutor):
         model_dict = paddle.load(self.ckpt_path)
         self.model.set_state_dict(model_dict)
 
-
     def preprocess(self, model_type: str, input: Union[str, os.PathLike]):
         """
         Input preprocess and return paddle.Tensor stored in self.input.

paddlespeech/cli/tts/infer.py

@@ -168,13 +168,13 @@ pretrained_models = {
     # mb_melgan
     "mb_melgan_csmsc-zh": {
         'url':
-        'https://paddlespeech.bj.bcebos.com/Parakeet/released_models/mb_melgan/mb_melgan_baker_finetune_ckpt_0.5.zip',
+        'https://paddlespeech.bj.bcebos.com/Parakeet/released_models/mb_melgan/mb_melgan_csmsc_ckpt_0.1.1.zip',
         'md5':
-        'b69322ab4ea766d955bd3d9af7dc5f2d',
+        'ee5f0604e20091f0d495b6ec4618b90d',
         'config':
-        'finetune.yaml',
+        'default.yaml',
         'ckpt':
-        'snapshot_iter_2000000.pdz',
+        'snapshot_iter_1000000.pdz',
         'speech_stats':
         'feats_stats.npy',
     },

paddlespeech/t2s/datasets/am_batch_fn.py

@@ -54,6 +54,7 @@ def speedyspeech_single_spk_batch_fn(examples):
     }
     return batch
 
+
 def speedyspeech_multi_spk_batch_fn(examples):
     # fields = ["phones", "tones", "num_phones", "num_frames", "feats", "durations"]
     phones = [np.array(item["phones"], dtype=np.int64) for item in examples]
@@ -95,6 +96,7 @@ def speedyspeech_multi_spk_batch_fn(examples):
         batch["spk_id"] = spk_id
     return batch
 
+
 def fastspeech2_single_spk_batch_fn(examples):
     # fields = ["text", "text_lengths", "speech", "speech_lengths", "durations", "pitch", "energy"]
     text = [np.array(item["text"], dtype=np.int64) for item in examples]

paddlespeech/t2s/exps/speedyspeech/preprocess.py

@@ -13,7 +13,6 @@
 # limitations under the License.
 import argparse
 import re
-import os
 from concurrent.futures import ThreadPoolExecutor
 from operator import itemgetter
 from pathlib import Path
@@ -32,8 +31,9 @@ from paddlespeech.t2s.data.get_feats import LogMelFBank
 from paddlespeech.t2s.datasets.preprocess_utils import compare_duration_and_mel_length
 from paddlespeech.t2s.datasets.preprocess_utils import get_phn_dur
 from paddlespeech.t2s.datasets.preprocess_utils import get_phones_tones
-from paddlespeech.t2s.datasets.preprocess_utils import merge_silence
 from paddlespeech.t2s.datasets.preprocess_utils import get_spk_id_map
+from paddlespeech.t2s.datasets.preprocess_utils import merge_silence
+
 
 def process_sentence(config: Dict[str, Any],
                      fp: Path,

paddlespeech/t2s/exps/speedyspeech/train.py

@@ -27,8 +27,8 @@ from paddle.io import DataLoader
 from paddle.io import DistributedBatchSampler
 from yacs.config import CfgNode
 
-from paddlespeech.t2s.datasets.am_batch_fn import speedyspeech_single_spk_batch_fn
 from paddlespeech.t2s.datasets.am_batch_fn import speedyspeech_multi_spk_batch_fn
+from paddlespeech.t2s.datasets.am_batch_fn import speedyspeech_single_spk_batch_fn
 from paddlespeech.t2s.datasets.data_table import DataTable
 from paddlespeech.t2s.models.speedyspeech import SpeedySpeech
 from paddlespeech.t2s.models.speedyspeech import SpeedySpeechEvaluator
@@ -58,7 +58,9 @@ def train_sp(args, config):
         f"rank: {dist.get_rank()}, pid: {os.getpid()}, parent_pid: {os.getppid()}",
     )
 
-    fields = ["phones", "tones", "num_phones", "num_frames", "feats", "durations"]
+    fields = [
+        "phones", "tones", "num_phones", "num_frames", "feats", "durations"
+    ]
 
     spk_num = None
     if args.speaker_dict is not None:
@@ -137,7 +139,10 @@ def train_sp(args, config):
     print("tone_size:", tone_size)
 
     model = SpeedySpeech(
-        vocab_size=vocab_size, tone_size=tone_size, spk_num=spk_num, **config["model"])
+        vocab_size=vocab_size,
+        tone_size=tone_size,
+        spk_num=spk_num,
+        **config["model"])
     if world_size > 1:
         model = DataParallel(model)
     print("model done!")

paddlespeech/t2s/models/speedyspeech/speedyspeech.py

@@ -14,7 +14,7 @@
 import numpy as np
 import paddle
 from paddle import nn
-import paddle.nn.functional as F
+
 from paddlespeech.t2s.modules.positional_encoding import sinusoid_position_encoding
 
 
@@ -95,8 +95,13 @@ class TextEmbedding(nn.Layer):
 
 
 class SpeedySpeechEncoder(nn.Layer):
-    def __init__(self, vocab_size, tone_size, hidden_size, kernel_size,
-                 dilations, spk_num=None):
+    def __init__(self,
+                 vocab_size,
+                 tone_size,
+                 hidden_size,
+                 kernel_size,
+                 dilations,
+                 spk_num=None):
         super().__init__()
         self.embedding = TextEmbedding(
             vocab_size,
@@ -104,7 +109,7 @@ class SpeedySpeechEncoder(nn.Layer):
             tone_size,
             padding_idx=0,
             tone_padding_idx=0)
-        
+
         if spk_num:
             self.spk_emb = nn.Embedding(
                 num_embeddings=spk_num,
@@ -112,7 +117,7 @@ class SpeedySpeechEncoder(nn.Layer):
                 padding_idx=0)
         else:
             self.spk_emb = None
-                
+
         self.prenet = nn.Sequential(
             nn.Linear(hidden_size, hidden_size),
             nn.ReLU(), )
@@ -171,19 +176,18 @@ class SpeedySpeechDecoder(nn.Layer):
 
 
 class SpeedySpeech(nn.Layer):
-    def __init__(
-            self,
-            vocab_size,
-            encoder_hidden_size,
-            encoder_kernel_size,
-            encoder_dilations,
-            duration_predictor_hidden_size,
-            decoder_hidden_size,
-            decoder_output_size,
-            decoder_kernel_size,
-            decoder_dilations,
-            tone_size=None, 
-            spk_num=None):
+    def __init__(self,
+                 vocab_size,
+                 encoder_hidden_size,
+                 encoder_kernel_size,
+                 encoder_dilations,
+                 duration_predictor_hidden_size,
+                 decoder_hidden_size,
+                 decoder_output_size,
+                 decoder_kernel_size,
+                 decoder_dilations,
+                 tone_size=None,
+                 spk_num=None):
         super().__init__()
         encoder = SpeedySpeechEncoder(vocab_size, tone_size,
                                       encoder_hidden_size, encoder_kernel_size,
@@ -255,6 +259,7 @@ class SpeedySpeech(nn.Layer):
         decoded = self.decoder(encodings)
         return decoded[0]
 
+
 class SpeedySpeechInference(nn.Layer):
     def __init__(self, normalizer, speedyspeech_model):
         super().__init__()

paddlespeech/t2s/models/speedyspeech/speedyspeech_updater.py

@@ -57,8 +57,7 @@ class SpeedySpeechUpdater(StandardUpdater):
             text=batch["phones"],
             tones=batch["tones"],
             durations=batch["durations"],
-            spk_id=spk_id
-            )
+            spk_id=spk_id)
 
         target_mel = batch["feats"]
         spec_mask = F.sequence_mask(
@@ -123,8 +122,7 @@ class SpeedySpeechEvaluator(StandardEvaluator):
             text=batch["phones"],
             tones=batch["tones"],
             durations=batch["durations"],
-            spk_id=spk_id
-            )
+            spk_id=spk_id)
 
         target_mel = batch["feats"]
         spec_mask = F.sequence_mask(