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97 lines
3.6 KiB
97 lines
3.6 KiB
([简体中文](./README_cn.md)|English)
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# ASR (Automatic Speech Recognition)
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## Introduction
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ASR, or Automatic Speech Recognition, refers to the problem of getting a program to automatically transcribe spoken language (speech-to-text).
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This demo is an implementation to recognize text from a specific audio file. It can be done by a single command or a few lines in python using `PaddleSpeech`.
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## Usage
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### 1. Installation
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see [installation](https://github.com/PaddlePaddle/PaddleSpeech/blob/develop/docs/source/install.md).
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You can choose one way from easy, meduim and hard to install paddlespeech.
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### 2. Prepare Input File
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The input of this demo should be a WAV file(`.wav`), and the sample rate must be the same as the model.
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Here are sample files for this demo that can be downloaded:
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```bash
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wget -c https://paddlespeech.bj.bcebos.com/PaddleAudio/zh.wav https://paddlespeech.bj.bcebos.com/PaddleAudio/en.wav
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```
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### 3. Usage
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- Command Line(Recommended)
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```bash
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# Chinese
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paddlespeech asr --input ./zh.wav -v
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# English
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paddlespeech asr --model transformer_librispeech --lang en --input ./en.wav -v
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# Chinese ASR + Punctuation Restoration
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paddlespeech asr --input ./zh.wav -v | paddlespeech text --task punc -v
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```
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(If you don't want to see the log information, you can remove "-v". Besides, it doesn't matter if package `paddlespeech-ctcdecoders` is not found, this package is optional.)
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Usage:
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```bash
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paddlespeech asr --help
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```
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Arguments:
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- `input`(required): Audio file to recognize.
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- `model`: Model type of asr task. Default: `conformer_wenetspeech`.
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- `lang`: Model language. Default: `zh`.
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- `sample_rate`: Sample rate of the model. Default: `16000`.
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- `config`: Config of asr task. Use pretrained model when it is None. Default: `None`.
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- `ckpt_path`: Model checkpoint. Use pretrained model when it is None. Default: `None`.
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- `yes`: No additional parameters required. Once set this parameter, it means accepting the request of the program by default, which includes transforming the audio sample rate. Default: `False`.
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- `device`: Choose device to execute model inference. Default: default device of paddlepaddle in current environment.
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- `verbose`: Show the log information.
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Output:
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```bash
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# Chinese
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[2021-12-08 13:12:34,063] [ INFO] [utils.py] [L225] - ASR Result: 我认为跑步最重要的就是给我带来了身体健康
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# English
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[2022-01-12 11:51:10,815] [ INFO] - ASR Result: i knocked at the door on the ancient side of the building
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```
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- Python API
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```python
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import paddle
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from paddlespeech.cli.asr import ASRExecutor
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asr_executor = ASRExecutor()
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text = asr_executor(
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model='conformer_wenetspeech',
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lang='zh',
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sample_rate=16000,
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config=None, # Set `config` and `ckpt_path` to None to use pretrained model.
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ckpt_path=None,
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audio_file='./zh.wav',
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force_yes=False,
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device=paddle.get_device())
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print('ASR Result: \n{}'.format(text))
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```
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Output:
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```bash
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ASR Result:
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我认为跑步最重要的就是给我带来了身体健康
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```
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### 4.Pretrained Models
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Here is a list of pretrained models released by PaddleSpeech that can be used by command and python API:
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| Model | Language | Sample Rate
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| :--- | :---: | :---: |
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| conformer_wenetspeech | zh | 16k
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| conformer_online_multicn | zh | 16k
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| conformer_aishell | zh | 16k
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| conformer_online_aishell | zh | 16k
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| transformer_librispeech | en | 16k
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| deepspeech2online_wenetspeech | zh | 16k
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| deepspeech2offline_aishell| zh| 16k
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| deepspeech2online_aishell | zh | 16k
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| deepspeech2offline_librispeech | en | 16k
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