Python connects to Alibaba Cloud interface to realize real-time audio transcoding function

Python connects to the Alibaba Cloud interface to implement real-time audio transcription function

Alibaba Cloud provides a wealth of artificial intelligence services, including speech recognition functions. With the help of Alibaba Cloud's API interface, we can use Python to implement real-time audio transcription function. This article will introduce how to connect to the Alibaba Cloud interface, use Python for real-time audio transcription, and provide code examples.

Step 1: Apply for Alibaba Cloud AccessKey

First, we need to register an account on the Alibaba Cloud official website and create an AccessKey to connect to the Alibaba Cloud API interface. On the Alibaba Cloud console page, select "AccessKey Management" to enter the AccessKey management page. Click the "Create AccessKey" button to obtain AccessKey and AccessKeySecret.

Step 2: Install Alibaba Cloud SDK

Next, we need to install Alibaba Cloud SDK to call Alibaba Cloud's speech recognition API interface. Open the command line and execute the following command to install the SDK:

pip install aliyun-python-sdk-core
pip install aliyunsdkcore

Step 3: Call the Alibaba Cloud real-time speech recognition API

In the code, we need to introduce the relevant libraries of the Alibaba Cloud SDK and set the AccessKey and AccessKeySecret:

from aliyunsdkcore.client import AcsClient
from aliyunsdkcore.profile import region_provider

accessKeyId = "your_access_key"
secret = "your_access_secret"

regionId = "cn-hangzhou"
region_provider.add_endpoint('asr', regionId, 'asr.aliyuncs.com')

client = AcsClient(accessKeyId, secret, regionId)

Next, we need to set the parameters and audio data for transcription recognition, and call the Alibaba Cloud API interface for real-time speech transcription:

import base64
import json

def transcribe_audio(audio_data):
    request = CommonRequest()
    request.set_domain('asr.cn-hangzhou.aliyuncs.com')
    request.set_version('2019-08-01')
    request.set_product('nls-filetrans')
    request.set_action_name('SubmitTask')

    audio_base64 = base64.b64encode(audio_data).decode('utf-8')
    task = {
        "app_key": accessKeyId,
        "file_link": "",
        "content": audio_base64,
        "enable_words": False,
        "enable_syllable": False,
        "enable_format": False,
        "enable_punctuation": False,
        "result_url": "",
        "result_format": "json"
    }
    request.add_body_params('task', json.dumps(task))

    response = client.do_action(request)
    result = json.loads(response.decode('utf-8'))
    taskId = result["data"]["taskId"]
    return taskId

In the above code, we Base64 is used to encode the audio data, and a request for API interface call is constructed, including accessKeyId, audio data and other transliteration parameters. We send a request by calling the do_action() method of AcsClient and obtain the task ID of real-time speech recognition.

Step 4: Obtain the real-time speech transcription results

After completing the real-time speech recognition task, we need to obtain the transcription results. Alibaba Cloud provides an API interface for querying task results. We can use this interface to poll to obtain task results.

def get_transcribe_result(taskId):
    request = CommonRequest()
    request.set_domain('asr.cn-hangzhou.aliyuncs.com')
    request.set_version('2019-08-01')
    request.set_product('nls-filetrans')
    request.set_action_name('GetTaskResult')

    request.add_query_param('taskId', taskId)

    response = client.do_action(request)
    result = json.loads(response.decode('utf-8'))
    if result["code"] == 200000:
        status = result["data"]["taskStatus"]
        if status == 'Success':
            result_url = result["data"]["result"]["resultUrl"]
            response = urllib.request.urlopen(result_url)
            transcript = response.read().decode('utf-8')
            return transcript
    return None

In the above code, we use polling to obtain the task results until the task is completed or times out. If the task completes successfully, we can get the URL of the transcribed result and use the urllib library to get the result.

Step 5: Run the real-time audio transcription code

In the main function, we can encapsulate the above steps into a function and pass in the audio data for transcription. We can read the audio data from the file and save the transcription results to the file.

def main():
    audio_path = "audio.wav"
    audio_data = read_audio_file(audio_path)

    taskId = transcribe_audio(audio_data)
    print("Task ID:", taskId)

    transcript = None
    while transcript is None:
        transcript = get_transcribe_result(taskId)
        time.sleep(2)

    transcript_path = "transcript.txt"
    with open(transcript_path, "w") as f:
        f.write(transcript)
    print("Transcript saved to:", transcript_path)

if __name__ == "__main__":
    main()

The above is a complete code example of the real-time audio transcription function. We can prepare the audio files to be transcribed, and after running the code, we can obtain the real-time transcribing results of the audio and save them to the specified file.

Summary

This article introduces how to use Python to connect to the Alibaba Cloud interface to implement real-time audio transcoding. By applying for the Alibaba Cloud AccessKey, installing the Alibaba Cloud SDK, and calling the Alibaba Cloud API interface, we can easily implement the real-time audio transcription function in Python. When using Alibaba Cloud API, we need to pay attention to parameter settings and result query to obtain accurate audio transcription results.

Appendix

The complete code example can be found on GitHub: [https://github.com/example/transcribe-python](https://github.com/example/transcribe- python)

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