Use Python programming to realize the docking of Baidu speech recognition interface, so that the program can accurately recognize speech

Use Python programming to implement the docking of Baidu’s speech recognition interface, so that the program can accurately recognize speech

In today’s technological development, speech recognition technology has been widely used each field. Baidu speech recognition is one of the most powerful speech recognition engines. By connecting to the Baidu speech recognition interface, we can use Python programming to implement speech recognition, so that the program can accurately recognize speech.

First of all, we need to prepare the following environment and materials:

1. Python programming environment (including pip environment);
2. App Key and Secret Key of Baidu Speech Recognition API ;
3. A voice file that needs to be recognized (supports multiple formats, such as wav, pcm, etc.).

Next, we will use Python programming to implement the docking of Baidu speech recognition interface.

First, we need to install the Python SDK for Baidu speech recognition. You can use the following command to install it:

pip install baidu-aip

After the installation is complete, we can use the following code example to connect to the Baidu speech recognition interface:

from aip import AipSpeech

# 设置百度语音识别的App Key、Secret Key和API版本
APP_ID = 'Your APP ID'
API_KEY = 'Your API Key'
SECRET_KEY = 'Your Secret Key'
VERSION = '2.0'

# 创建AipSpeech对象
client = AipSpeech(APP_ID, API_KEY, SECRET_KEY)

# 调用百度语音识别接口
def speech_to_text(file_path):
    with open(file_path, 'rb') as fp:
        speech_data = fp.read()
        result = client.asr(speech_data, 'pcm', 16000, {
            'dev_pid': '1536',
        })
        if 'result' in result.keys():
            return result['result'][0]
        else:
            return '识别失败'

# 测试代码
file_path = 'test.wav'
text = speech_to_text(file_path)
print(text)

In the above code, we first imported the AipSpeech class, and then set the App Key, Secret Key and API version of Baidu speech recognition. Next, the AipSpeech object is created and the speech_to_text function is defined, which is used to call the Baidu speech recognition interface to implement the speech recognition function. Finally, we use test.wav as the test file, call the speech_to_text function to recognize the speech file, and print the results.

It should be noted that when calling the Baidu speech recognition interface, the parameters we need to pass in include voice file data, voice file format (pcm), sampling rate (16000) and voice model (dev_pid). In the sample code, we set the speech model to 1536, which is suitable for recognizing Mandarin Chinese.

Through the above code examples, we can easily connect to the Baidu speech recognition interface to achieve accurate speech recognition by the program. Of course, in practical applications, we can also process and judge the results according to needs to meet specific needs.

To sum up, the connection with Baidu’s speech recognition interface is realized through Python programming, so that the program can accurately recognize speech, which provides convenience for us to develop speech recognition-related applications in practice. I hope the introduction in this article is helpful to you!

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