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README.md
(简体中文|English)
TTS (Text To Speech)
Introduction
Text-to-speech (TTS) is a natural language modeling process that requires changing units of text into units of speech for audio presentation.
This demo is an implementation to generate audio from the given text. It can be done by a single command or a few lines in python using PaddleSpeech
.
Usage
1. Installation
see https://github.com/PaddlePaddle/PaddleSpeech/blob/develop/docs/source/install.md.
You can choose one way from easy, meduim and hard to install paddlespeech.
2. Prepare Input
The input of this demo should be a text of the specific language that can be passed via argument.
3. Usage
-
Command Line (Recommended)
-
Chinese
The default acoustic model is
Fastspeech2
, and the default vocoder isParallel WaveGAN
.paddlespeech tts --input "你好,欢迎使用百度飞桨深度学习框架!"
-
Chinese, use
SpeedySpeech
as the acoustic modelpaddlespeech tts --am speedyspeech_csmsc --input "你好,欢迎使用百度飞桨深度学习框架!"
-
Chinese, multi-speaker
You can change
spk_id
here.paddlespeech tts --am fastspeech2_aishell3 --voc pwgan_aishell3 --input "你好,欢迎使用百度飞桨深度学习框架!" --spk_id 0
-
English
paddlespeech tts --am fastspeech2_ljspeech --voc pwgan_ljspeech --lang en --input "hello world"
-
English, multi-speaker
You can change
spk_id
here.paddlespeech tts --am fastspeech2_vctk --voc pwgan_vctk --input "hello, boys" --lang en --spk_id 0
Usage:
paddlespeech tts --help
Arguments:
input
(required): Input text to generate..am
: Acoustic model type of tts task. Default:fastspeech2_csmsc
.am_config
: Config of acoustic model. Use deault config when it is None. Default:None
.am_ckpt
: Acoustic model checkpoint. Use pretrained model when it is None. Default:None
.am_stat
: Mean and standard deviation used to normalize spectrogram when training acoustic model. Default:None
.phones_dict
: Phone vocabulary file. Default:None
.tones_dict
: Tone vocabulary file. Default:None
.speaker_dict
: speaker id map file. Default:None
.spk_id
: Speaker id for multi speaker acoustic model. Default:0
.voc
: Vocoder type of tts task. Default:pwgan_csmsc
.voc_config
: Config of vocoder. Use deault config when it is None. Default:None
.voc_ckpt
: Vocoder checkpoint. Use pretrained model when it is None. Default:None
.voc_stat
: Mean and standard deviation used to normalize spectrogram when training vocoder. Default:None
.lang
: Language of tts task. Default:zh
.device
: Choose device to execute model inference. Default: default device of paddlepaddle in current environment.output
: Output wave filepath. Default:output.wav
.
Output:
[2021-12-09 20:49:58,955] [ INFO] [log.py] [L57] - Wave file has been generated: output.wav
-
-
Python API
import paddle from paddlespeech.cli import TTSExecutor tts_executor = TTSExecutor() wav_file = tts_executor( text='今天的天气不错啊', output='output.wav', am='fastspeech2_csmsc', am_config=None, am_ckpt=None, am_stat=None, spk_id=0, phones_dict=None, tones_dict=None, speaker_dict=None, voc='pwgan_csmsc', voc_config=None, voc_ckpt=None, voc_stat=None, lang='zh', device=paddle.get_device()) print('Wave file has been generated: {}'.format(wav_file))
Output:
Wave file has been generated: output.wav
4. Pretrained Models
Here is a list of pretrained models released by PaddleSpeech that can be used by command and python API:
-
Acoustic model
Model Language speedyspeech_csmsc zh fastspeech2_csmsc zh fastspeech2_aishell3 zh fastspeech2_ljspeech en fastspeech2_vctk en -
Vocoder
Model Language pwgan_csmsc zh pwgan_aishell3 zh pwgan_ljspeech en pwgan_vctk en mb_melgan_csmsc zh