PaddleSpeech/demos/audio_content_search

(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 requirements.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. run paddlespeech_server

Before using the client, it is necessary to start paddlespeech_servers.

Here are sample server configuration：

bash demos/audio_content_search/run.sh

The logs of the two services will be recorded in 'acs.log' and 'streaming_asr.log' in this configuration.

4. Usage

• Command Line(Recommended)

  # Chinese
  paddlespeech_client acs --server_ip 127.0.0.1 --port 8490 --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}]}