(简体中文|English)
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
.
see installation.
You can choose one way from easy, meduim and hard to install paddlespeech.
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:
wget -c https://paddlespeech.bj.bcebos.com/PaddleAudio/zh.wav https://paddlespeech.bj.bcebos.com/PaddleAudio/en.wav https://paddlespeech.bj.bcebos.com/PaddleAudio/ch_zh_mix.wav
-
Command Line(Recommended)
# Chinese paddlespeech asr --input ./zh.wav -v # English paddlespeech asr --model transformer_librispeech --lang en --input ./en.wav -v # Code-Switch paddlespeech asr --model conformer_talcs --lang zh_en --codeswitch True --input ./ch_zh_mix.wav -v # Chinese ASR + Punctuation Restoration paddlespeech asr --input ./zh.wav -v | paddlespeech text --task punc -v
(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.)Usage:
paddlespeech asr --help
Arguments:
input
(required): Audio file to recognize.model
: Model type of asr task. Default:conformer_wenetspeech
.lang
: Model language. Default:zh
.codeswitch
: Code Swith Model. Default:False
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
.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
.device
: Choose device to execute model inference. Default: default device of paddlepaddle in current environment.verbose
: Show the log information.
Output:
# Chinese [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 # English [2022-01-12 11:51:10,815] [ INFO] - ASR Result: i knocked at the door on the ancient side of the building
-
Python API
import paddle from paddlespeech.cli.asr 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', force_yes=False, device=paddle.get_device()) print('ASR Result: \n{}'.format(text))
Output:
ASR Result: 我认为跑步最重要的就是给我带来了身体健康
Here is a list of pretrained models released by PaddleSpeech that can be used by command and python API:
Model | Code Switch | Language | Sample Rate |
---|---|---|---|
conformer_wenetspeech | False | zh | 16k |
conformer_online_multicn | False | zh | 16k |
conformer_aishell | False | zh | 16k |
conformer_online_aishell | False | zh | 16k |
transformer_librispeech | False | en | 16k |
deepspeech2online_wenetspeech | False | zh | 16k |
deepspeech2offline_aishell | False | zh | 16k |
deepspeech2online_aishell | False | zh | 16k |
deepspeech2offline_librispeech | False | en | 16k |
conformer_talcs | True | zh_en | 16k |