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PaddleSpeech/demos/audio_content_search
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README.md remove old vector model info, test=doc 2 years ago
README_cn.md remove old vector model info, test=doc 2 years ago
acs_clinet.py
requirements.txt
run.sh
streaming_asr_server.py

README.md

(简体中文|English)

ACS (Audio Content Search)

Introduction

ACS, or Audio Content Search, refers to the problem of getting the key word time stamp from automatically transcribe spoken language (speech-to-text).

This demo is an implementation of obtaining the keyword timestamp in the text from a given audio file. It can be done by a single command or a few lines in python using PaddleSpeech. Now, the search word in demo is:

我
康

Usage

1. Installation

see installation.

You can choose one way from meduim and hard to install paddlespeech.

The dependency refers to the requirements.txt, and install the dependency as follows:

pip install -r requriement.txt 

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:

wget -c https://paddlespeech.bj.bcebos.com/PaddleAudio/zh.wav

3. Usage

  • Command Line(Recommended)

    # Chinese
    paddlespeech_client acs --server_ip 127.0.0.1 --port 8090 --input ./zh.wav 
    

    Usage:

    paddlespeech asr --help
    

    Arguments:

    • input(required): Audio file to recognize.
    • server_ip: the server ip.
    • port: the server port.
    • lang: the language type of the model. Default: zh.
    • sample_rate: Sample rate of the model. Default: 16000.
    • audio_format: The audio format.

    Output:

    [2022-05-15 15:00:58,185] [    INFO] - acs http client start
    [2022-05-15 15:00:58,185] [    INFO] - endpoint: http://127.0.0.1:8490/paddlespeech/asr/search
    [2022-05-15 15:01:03,220] [    INFO] - acs http client finished
    [2022-05-15 15:01:03,221] [    INFO] - ACS result: {'transcription': '我认为跑步最重要的就是给我带来了身体健康', 'acs': [{'w': '我', 'bg': 0, 'ed': 1.6800000000000002}, {'w': '我', 'bg': 2.1, 'ed': 4.28}, {'w': '康', 'bg': 3.2, 'ed': 4.92}]}
    [2022-05-15 15:01:03,221] [    INFO] - Response time 5.036084 s.
    
  • Python API

    from paddlespeech.server.bin.paddlespeech_client import ACSClientExecutor
    
    acs_executor = ACSClientExecutor()
    res = acs_executor(
        input='./zh.wav',
        server_ip="127.0.0.1",
        port=8490,)
    print(res)
    

    Output:

    [2022-05-15 15:08:13,955] [    INFO] - acs http client start
    [2022-05-15 15:08:13,956] [    INFO] - endpoint: http://127.0.0.1:8490/paddlespeech/asr/search
    [2022-05-15 15:08:19,026] [    INFO] - acs http client finished
    {'transcription': '我认为跑步最重要的就是给我带来了身体健康', 'acs': [{'w': '我', 'bg': 0, 'ed': 1.6800000000000002}, {'w': '我', 'bg': 2.1, 'ed': 4.28}, {'w': '康', 'bg': 3.2, 'ed': 4.92}]}