How to use uniapp to develop speech recognition function

How to use uniapp to develop speech recognition function

The popularity and application of speech technology are becoming more and more extensive, and speech recognition has become one of the important functions of many applications. In the uniapp framework, we can use the cross-platform capabilities provided by uniapp to quickly develop applications with speech recognition capabilities. This article will introduce how to use uniapp to develop speech recognition functions and provide corresponding code examples.

1. Preparation
Before starting, we need to ensure that the uniapp development environment has been installed and introduce the uniapp plug-in that supports speech recognition into the project.

1. Install the uniapp development environment: Choose the appropriate development tool according to your operating system, such as HBuilderX.
2. Introducing the speech recognition plug-in: Click "Plug-in Market" in HBuilderX, search and install the "uni-speech-recognition" plug-in. This plug-in is the speech recognition plug-in officially recommended by uniapp, which can help us quickly implement the speech recognition function.

2. Implement the speech recognition function
After completing the preparatory work, we can start to implement the speech recognition function. The following are the steps and code examples to implement the speech recognition function:

1. Create page: Create a new page in the uniapp project, such as "voiceRecognition".

2. Introduce the plug-in: In the created page, introduce the speech recognition plug-in provided by uniapp. The code is as follows:

   import uniSpeechRecognition from '@/uni-speech-recognition/uni-speech-recognition.js'; // 引入语音识别插件

3. Configure permissions: In order to use speech recognition normally function, we need to configure permissions in the manifest.json file, the code is as follows:

   "permission": {
     "scope.userLocation": {
    "desc": "用于语音识别"
     }
   }

4. Initialize speech recognition: In the life cycle of the page, use the following code to initialize the speech recognition function and bind it Define the relevant event callback function:

   export default {
     onLoad() {
    uniSpeechRecognition.init(); // 初始化语音识别
   
    // 绑定语音识别结束事件回调函数
    uniSpeechRecognition.onStop(res => {
      console.log('识别结果：', res.result);
    });
   
    // 绑定语音识别错误事件回调函数
    uniSpeechRecognition.onError(res => {
      console.error('识别错误：', res.errMsg);
    });
     }
   }

5. Start speech recognition: Where you need to start speech recognition, call the following code to start speech recognition:

   uniSpeechRecognition.start({
     lang: 'zh_CN', // 语种，默认为中文
     timeout: 5000 // 超时时间，默认为5秒
   });

6. Stop speech recognition: When there is no need to continue to recognize speech, you can call the following code to stop speech recognition:

   uniSpeechRecognition.stop();

3. Test the speech recognition function
After completing the above After these steps, we can test the speech recognition function on the "voiceRecognition" page in the uniapp project. Start speech recognition by clicking the button, click the button again to stop speech recognition, and then you can view the recognition results on the console.

<template>
  <view>
    <button @click="startRecognition">开始识别</button>
    <button @click="stopRecognition">停止识别</button>
  </view>
</template>

<script>
  import uniSpeechRecognition from '@/uni-speech-recognition/uni-speech-recognition.js';

  export default {
    methods: {
      startRecognition() {
        uniSpeechRecognition.start({
          lang: 'zh_CN',
          timeout: 5000
        });
      },
      stopRecognition() {
        uniSpeechRecognition.stop();
      },
    },
    onLoad() {
      uniSpeechRecognition.init();

      uniSpeechRecognition.onStop(res => {
        console.log('识别结果：', res.result);
      });

      uniSpeechRecognition.onError(res => {
        console.error('识别错误：', res.errMsg);
      });
    }
  }
</script>

Through the above steps, we successfully implemented the speech recognition function in uniapp and provided corresponding code examples for reference. I hope this article can be helpful to everyone in using uniapp to develop speech recognition functions.

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