Teach you step-by-step how to use Python to connect to the Qiniu Cloud interface to realize the audio-to-text function

Teach you step by step how to use Python to connect to the Qiniu Cloud interface to realize the audio-to-text function

With the continuous development of artificial intelligence technology, the demand for audio-to-text conversion is increasing. As a leading cloud service provider in China, Qiniu Cloud provides a series of rich interfaces to facilitate developers to implement the audio-to-text function in their own applications. This article will teach you step by step how to use Python to connect to the Qiniu Cloud interface to realize the audio-to-text function.

First of all, you need to register a Qiniu Cloud account and obtain the access key, including Access Key and Secret Key. Then, you need to install the corresponding Python libraries, including qiniu and requests libraries. It can be installed using the pip command.

pip install qiniu
pip install requests

Next, we start writing code. First introduce the required libraries:

import requests
from qiniu import Auth

Then, set your Access Key and Secret Key:

access_key = 'your_access_key'
secret_key = 'your_secret_key'

Then, create an Auth object:

q = Auth(access_key, secret_key)

Now, we can The audio-to-text function has begun to be implemented. First, we need to upload the audio file to Qiniu Cloud and obtain the URL of the file. The code is as follows:

def upload_audio(filepath):
    bucket_name = 'your_bucket_name'
    key = 'your_file_key'

    token = q.upload_token(bucket_name, key, 3600)
    ret, info = upload_file(token, key, filepath)
    url = 'http://your_domain/' + ret['key']
    return url

def upload_file(token, key, filepath):
    data = {'token': token, 'key': key}
    files = {'file': open(filepath, 'rb')}
    response = requests.post('http://upload.qiniup.com', data=data, files=files)
    ret = response.json()
    return ret, response

Next, we need to call Qiniu Cloud’s audio-to-text interface to convert the uploaded audio file into text. The code is as follows:

def audio_to_text(audio_url):
    url = 'http://api.qiniu.com/v1/speech/word'
    headers = {'Content-Type': 'application/x-www-form-urlencoded'}
    body = {'url': audio_url, 'language': 'zh-Hans'}

    response = requests.post(url, headers=headers, data=body)
    ret = response.json()
    return ret

Finally, we can write a simple test function to connect the whole process together:

def test():
    audio_filepath = 'your_audio_file_path'
    url = upload_audio(audio_filepath)
    ret = audio_to_text(url)
    print(ret)

At this point, we have completed using Python to connect to the Qiniu Cloud interface to implement audio conversion Code for the text function. You can save the above code in a .py file and run the test function to verify it.

It should be noted that Qiniu Cloud’s interface has some restrictions, including the size and duration of audio files, etc. Please pay attention to comply with relevant regulations during use.

To summarize, this article uses specific code examples to teach you step by step how to use Python to connect to the Qiniu Cloud interface to implement the audio-to-text function. I hope it can be helpful to you in the development process!

The above is the detailed content of Teach you step-by-step how to use Python to connect to the Qiniu Cloud interface to realize the audio-to-text function. For more information, please follow other related articles on the PHP Chinese website!