([简体中文](./README_cn.md)|English) # ASR (Automatic Speech Recognition) ## Introduction ASR, or Automatic Speech Recognition, refers to the problem of getting a program to automatically transcribe spoken language (speech-to-text). 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`. ## Usage ### 1. Installation ```bash pip install paddlespeech ``` ### 2. Prepare Input File The input of this demo should be a WAV file(`.wav`), and the sample rate must be the same as the model. Here are sample files for this demo that can be downloaded: ```bash wget -c https://paddlespeech.bj.bcebos.com/PaddleAudio/zh.wav https://paddlespeech.bj.bcebos.com/PaddleAudio/en.wav ``` ### 3. Usage - Command Line(Recommended) ```bash paddlespeech asr --input ./zh.wav ``` Usage: ```bash paddlespeech asr --help ``` Arguments: - `input`(required): Audio file to recognize. - `model`: Model type of asr task. Default: `conformer_wenetspeech`. - `lang`: Model language. Default: `zh`. - `sample_rate`: Sample rate of the model. Default: `16000`. - `config`: Config of asr task. Use pretrained model when it is None. Default: `None`. - `ckpt_path`: Model checkpoint. Use pretrained model when it is None. Default: `None`. - `device`: Choose device to execute model inference. Default: default device of paddlepaddle in current environment. Output: ```bash [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 ``` - Python API ```python import paddle from paddlespeech.cli import ASRExecutor asr_executor = ASRExecutor() text = asr_executor( model='conformer_wenetspeech', lang='zh', sample_rate=16000, config=None, # Set `config` and `ckpt_path` to None to use pretrained model. ckpt_path=None, audio_file='./zh.wav', device=paddle.get_device()) print('ASR Result: \n{}'.format(text)) ``` Output: ```bash ASR Result: 我认为跑步最重要的就是给我带来了身体健康 ``` ### 4.Pretrained Models Here is a list of pretrained models released by PaddleSpeech that can be used by command and python API: | Model | Language | Sample Rate | :--- | :---: | :---: | | conformer_wenetspeech| zh| 16000