Home Web Front-end uni-app Use uniapp to implement speech recognition function

Use uniapp to implement speech recognition function

Nov 21, 2023 pm 12:58 PM
uniapp Speech Recognition accomplish

Use uniapp to implement speech recognition function

Using uniapp to implement the speech recognition function requires specific code examples

With the rapid development of intelligent technology, speech recognition technology has attracted more and more attention and application. The speech recognition function is implemented using the uniapp framework, which can be easily deployed and used on multiple platforms. This article will introduce how to use the uniapp framework to implement speech recognition functions and provide specific code examples.

1. Preparation
Before starting, we need to install the uniapp development environment and create a uniapp project. For specific installation and project creation operations, please refer to the uniapp official documentation. After creating the project, we need to introduce the speech recognition plug-in.

  1. In HBuilderX, click "Plug-in" - "Plug-in Management" in the menu bar.
  2. Search for "speech recognition" in the plug-in management interface and install it.
  3. After the installation is complete, we can find the added plug-ins in the manifest.json file of the project.

2. Implement the speech recognition function
Let’s write code to implement the speech recognition function. In the uniapp framework, you can use the API provided by the plug-in for voice recording and speech recognition.

  1. Create a button in the page where you need to add speech recognition function, and add the following code in the button's click event:
// 开始录制语音
uni.startRecord({
    success: function(res) {
        console.log('录音成功');
    }
});
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  1. Continue in the button's click event Add the following code to the click event to implement the voice recognition function after recording:
// 结束录制语音
uni.stopRecord({
    success: function(res) {
        console.log('录音结束');
        // 获取录音文件的临时路径
        var tempFilePath = res.tempFilePath;
        // 调用语音识别的API进行识别
        uni.recognizeVoice({
            filePath: tempFilePath,
            success: function(res) {
                console.log('语音识别结果:' + res.result);
            }
        });
    }
});
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The above code implements the functions of recording voice and recognizing voice. When the user clicks the button, uniapp will call the system's recording function to record, then end the recording, and pass the temporary path of the recording file to the speech recognition API for recognition, and finally output the recognition result to the console.

3. Testing and debugging
After completing the code writing, we can directly run the uniapp project in HBuilderX for testing and debugging. Click the button on the simulator or real device to perform voice recording and recognition, and then view the recognition results output by the console.

It should be noted that before performing voice recording and recognition, you need to be authorized to use the recording function. In the uniapp framework, permission acquisition and judgment can be achieved through the uni.requestAuth method.

uni.requestAuth({
    scope: 'scope.record',
    success: function(res) {
        console.log('录音权限授权成功');
    },
    fail: function(res) {
        console.log('录音权限授权失败');
    }
});
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The above code will trigger the system's permission request box. The user needs to confirm the authorization to use the recording function before voice recording and recognition can be performed.

Summary:
This article introduces the steps to implement speech recognition function using the uniapp framework, and provides specific code examples. By using the plug-ins and APIs provided by uniapp, we can easily implement voice recording and recognition functions on multiple platforms. Through the above code examples and testing and debugging, I believe that readers have a certain understanding and mastery of the speech recognition function implemented by uniapp. I hope this article is helpful to readers, thank you for reading!

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