Use Python to connect with Tencent Cloud interface to realize real-time speech transcription function

Use Python to interface with Tencent Cloud to realize real-time speech transcription function

In recent years, with the rapid development of artificial intelligence technology, speech recognition technology has also received increasing attention. As a leading cloud service provider in China, Tencent Cloud provides a wealth of speech recognition interfaces, including real-time speech transcription interfaces. This article will introduce how to use Python to connect with Tencent Cloud interface to realize real-time speech transcription function.

First, we need to apply for an API key on the Tencent Cloud official website and obtain the access key to the Tencent Cloud API. After obtaining the access key, we can use Python's requests library to make interface requests.

Next, we need to install Python’s requests library. It can be installed through the following command:

pip install requests

After the installation is completed, we can write code. The following is a simple example:

import requests
import json

def recognize_speech(audio_file, secret_id, secret_key):
    # 设置请求地址及参数
    url = 'https://s.tencentcloudapi.com/'
    params = {
        'Action': 'CreateASRTask',
        'Version': '2019-12-12',
        'Region': 'ap-guangzhou',
        'Timestamp': int(time.time()),
        'Nonce': random.randint(1, 10000),
        'SecretId': secret_id,
        'SignatureMethod': 'HmacSHA256',
    }

    # 计算签名
    sorted_params = sorted(params.items(), key=lambda x: x[0])
    query_string = urlencode(sorted_params, quote_via=quote_plus)
    src_str = 'POSTs.tencentcloudapi.com/?' + query_string
    signature = base64.b64encode(hmac.new(secret_key.encode('utf-8'), src_str.encode('utf-8'), hashlib.sha256).digest()).decode('utf-8')
    params['Signature'] = signature

    # 读取音频文件
    with open(audio_file, 'rb') as f:
        file_content = base64.b64encode(f.read()).decode('utf-8')

    # 构造请求数据
    data = {
        'TaskConfig': {
            'EngineModelType': '16k_zh',
        },
        'Data': {
            'Url': '',
            'Data': file_content,
        },
    }

    # 发送请求
    response = requests.post(url, data=json.dumps(data), params=params)

    # 解析返回结果
    result = json.loads(response.text)
    return result

if __name__ == '__main__':
    audio_file = 'test.wav'
    secret_id = 'your_secret_id'
    secret_key = 'your_secret_key'
    result = recognize_speech(audio_file, secret_id, secret_key)
    print(result)

In this example, we define a recognize_speech function that accepts the audio file path, the SecretId and SecretKey of Tencent Cloud API as parameters. The function uploads the audio file to Tencent Cloud by sending a POST request and returns the transcription result.

It should be noted that before calling the recognize_speech function, the audio file needs to be prepared, and the path of the audio file, the SecretId and SecretKey of Tencent Cloud API need to be passed to the function.

The above is a simple example of using Python to connect with the Tencent Cloud interface to realize the real-time speech transcription function. By calling Tencent Cloud's API, we can easily implement the audio transcription function, providing a convenient and fast solution for the application of speech recognition technology. I hope this article can help you use Python to connect the real-time speech transcription function with the Tencent Cloud interface in practice.

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