metadata
tags:
- tensorflowtts
- audio
- text-to-speech
- text-to-mel
language: chinese
license: apache-2.0
datasets:
- Baker
widget:
- text: 这是一个开源的端到端中文语音合成系统
FastSpeech2 trained on Baker (Chinese)
This repository provides a pretrained FastSpeech2 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:
pip install TensorFlowTTS
Converting your Text to Mel Spectrogram
import numpy as np
import soundfile as sf
import yaml
import tensorflow as tf
from tensorflow_tts.inference import AutoProcessor
from tensorflow_tts.inference import TFAutoModel
processor = AutoProcessor.from_pretrained("tensorspeech/tts-fastspeech2-baker-ch")
fastspeech2 = TFAutoModel.from_pretrained("tensorspeech/tts-fastspeech2-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)
mel_before, mel_after, duration_outputs, _, _ = fastspeech2.inference(
input_ids=tf.expand_dims(tf.convert_to_tensor(input_ids, dtype=tf.int32), 0),
speaker_ids=tf.convert_to_tensor([0], dtype=tf.int32),
speed_ratios=tf.convert_to_tensor([1.0], dtype=tf.float32),
f0_ratios =tf.convert_to_tensor([1.0], dtype=tf.float32),
energy_ratios =tf.convert_to_tensor([1.0], dtype=tf.float32),
)
Referencing FastSpeech2
@misc{ren2021fastspeech,
title={FastSpeech 2: Fast and High-Quality End-to-End Text to Speech},
author={Yi Ren and Chenxu Hu and Xu Tan and Tao Qin and Sheng Zhao and Zhou Zhao and Tie-Yan Liu},
year={2021},
eprint={2006.04558},
archivePrefix={arXiv},
primaryClass={eess.AS}
}
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}},
}