You can not select more than 25 topics
Topics must start with a letter or number, can include dashes ('-') and can be up to 35 characters long.
126 lines
4.3 KiB
126 lines
4.3 KiB
([简体中文](./README_cn.md)|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 [installation](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 is `Parallel WaveGAN`.
|
|
```bash
|
|
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 model
|
|
```bash
|
|
paddlespeech 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.
|
|
```bash
|
|
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
|
|
```bash
|
|
paddlespeech tts --am fastspeech2_ljspeech --voc pwgan_ljspeech --lang en --input "hello world"
|
|
```
|
|
- English, multi-speaker
|
|
|
|
You can change `spk_id` here.
|
|
```bash
|
|
paddlespeech tts --am fastspeech2_vctk --voc pwgan_vctk --input "hello, boys" --lang en --spk_id 0
|
|
```
|
|
Usage:
|
|
|
|
```bash
|
|
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:
|
|
```bash
|
|
[2021-12-09 20:49:58,955] [ INFO] [log.py] [L57] - Wave file has been generated: output.wav
|
|
```
|
|
|
|
- Python API
|
|
```python
|
|
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:
|
|
```bash
|
|
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
|