
# Multi-band MelGAN trained on Baker (Ch)
This repository provides a pretrained [Multi-band MelGAN](https://arxiv.org/abs/2005.05106) trained on Baker dataset (ch). For a detail of the model, we encourage you to read more about
[TensorFlowTTS](https://github.com/TensorSpeech/TensorFlowTTS). 


## Install TensorFlowTTS
First of all, please install TensorFlowTTS with the following command:
```
pip install TensorFlowTTS
```

### Converting your Text to Wav
```python
import soundfile as sf
import numpy as np

import tensorflow as tf

from tensorflow_tts.inference import AutoProcessor
from tensorflow_tts.inference import TFAutoModel

processor = AutoProcessor.from_pretrained("tensorspeech/tts-tacotron2-baker-ch")
tacotron2 = TFAutoModel.from_pretrained("tensorspeech/tts-tacotron2-baker-ch")
mb_melgan = TFAutoModel.from_pretrained("tensorspeech/tts-mb_melgan-baker-ch")

text = "这是一个开源的端到端中文语音合成系统"

input_ids = processor.text_to_sequence(text, inference=True)

# tacotron2 inference (text-to-mel)
decoder_output, mel_outputs, stop_token_prediction, alignment_history = tacotron2.inference(
    input_ids=tf.expand_dims(tf.convert_to_tensor(input_ids, dtype=tf.int32), 0),
    input_lengths=tf.convert_to_tensor([len(input_ids)], tf.int32),
    speaker_ids=tf.convert_to_tensor([0], dtype=tf.int32),
)

# melgan inference (mel-to-wav)
audio = mb_melgan.inference(mel_outputs)[0, :, 0]

# save to file
sf.write('./audio.wav', audio, 22050, "PCM_16")
```

#### Referencing Multi-band MelGAN
```
@misc{yang2020multiband,
      title={Multi-band MelGAN: Faster Waveform Generation for High-Quality Text-to-Speech}, 
      author={Geng Yang and Shan Yang and Kai Liu and Peng Fang and Wei Chen and Lei Xie},
      year={2020},
      eprint={2005.05106},
      archivePrefix={arXiv},
      primaryClass={cs.SD}
}
```

#### Referencing TensorFlowTTS
```
@misc{TFTTS,
    author = {Minh Nguyen, Alejandro Miguel Velasquez, Erogol, Kuan Chen, Dawid Kobus, Takuya Ebata, 
    Trinh Le and Yunchao He},
    title = {TensorflowTTS},
    year = {2020},
    publisher = {GitHub},
    journal = {GitHub repository},
    howpublished = {\\url{https://github.com/TensorSpeech/TensorFlowTTS}},
  }
```
{"language": "ch", "license": "apache-2.0", "tags": ["tensorflowtts", "audio", "text-to-speech", "mel-to-wav"], "datasets": ["Baker"], "widget": [{"text": "\u8fd9\u662f\u4e00\u4e2a\u5f00\u6e90\u7684\u7aef\u5230\u7aef\u4e2d\u6587\u8bed\u97f3\u5408\u6210\u7cfb\u7edf"}]}
tensorflowtts audio text-to-speech mel-to-wav ch dataset:Baker arxiv:2005.05106 license:apache-2.0 has_space region:us
TAGS
#tensorflowtts #audio #text-to-speech #mel-to-wav #ch #dataset-Baker #arxiv-2005.05106 #license-apache-2.0 #has_space #region-us 


# Multi-band MelGAN trained on Baker (Ch)
This repository provides a pretrained Multi-band MelGAN trained on Baker dataset (ch). For a detail of the model, we encourage you to read more about
TensorFlowTTS. 


## Install TensorFlowTTS
First of all, please install TensorFlowTTS with the following command:


### Converting your Text to Wav


#### Referencing Multi-band MelGAN


#### Referencing TensorFlowTTS

# Multi-band MelGAN trained on Baker (Ch)
This repository provides a pretrained Multi-band MelGAN trained on Baker dataset (ch). For a detail of the model, we encourage you to read more about
TensorFlowTTS. ## Install TensorFlowTTS
First of all, please install TensorFlowTTS with the following command: ### Converting your Text to Wav #### Referencing Multi-band MelGAN #### Referencing TensorFlowTTS
TAGS
#tensorflowtts #audio #text-to-speech #mel-to-wav #ch #dataset-Baker #arxiv-2005.05106 #license-apache-2.0 #has_space #region-us 
 # Multi-band MelGAN trained on Baker (Ch)
This repository provides a pretrained Multi-band MelGAN trained on Baker dataset (ch). For a detail of the model, we encourage you to read more about
TensorFlowTTS. ## Install TensorFlowTTS
First of all, please install TensorFlowTTS with the following command: ### Converting your Text to Wav #### Referencing Multi-band MelGAN #### Referencing TensorFlowTTS
passage: TAGS
#tensorflowtts #audio #text-to-speech #mel-to-wav #ch #dataset-Baker #arxiv-2005.05106 #license-apache-2.0 #has_space #region-us 
# Multi-band MelGAN trained on Baker (Ch)
This repository provides a pretrained Multi-band MelGAN trained on Baker dataset (ch). For a detail of the model, we encourage you to read more about
TensorFlowTTS.## Install TensorFlowTTS
First of all, please install TensorFlowTTS with the following command:### Converting your Text to Wav#### Referencing Multi-band MelGAN#### Referencing TensorFlowTTS