Home Backend Development Python Tutorial Practical experience of connecting Python and Baidu intelligent voice interface

Practical experience of connecting Python and Baidu intelligent voice interface

Aug 12, 2023 am 10:51 AM
python Baidu Intelligent voice

Practical experience of connecting Python and Baidu intelligent voice interface

Practical experience in connecting Python and Baidu intelligent voice interface

Introduction:
With the continuous development of artificial intelligence technology, speech recognition is an important part of it. , has been widely used in various fields, such as voice assistants, voice translation, voice interaction, etc. As an efficient and accurate speech recognition service, Baidu Intelligent Voice Interface is very convenient and easy to use for developers. This article will introduce how to use Python to connect with Baidu Intelligent Voice Interface and provide relevant code examples.

1. Apply for Baidu Intelligent Voice Interface
First, we need to apply for an account and log in to the official Baidu Intelligent Cloud website. Then create a new application in the console and apply for the API Key and Secret Key to access Baidu Intelligent Voice Interface.

2. Install dependent libraries
Before using Python to connect with Baidu Intelligent Voice Interface, we need to install the relevant dependent libraries first. Open the command line tool and use the following command to install the required dependent libraries:

pip install baidu-aip
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3. Create a Python script file
Create a new Python script file and import the relevant libraries in the script file:

from aip import AipSpeech
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4. Initialize the Baidu Intelligent Voice Interface Client
In the Python script, use the API Key and Secret Key previously applied to initialize the Baidu Intelligent Voice Interface Client:

APP_ID = 'Your_APP_ID'
API_KEY = 'Your_API_KEY'
SECRET_KEY = 'Your_SECRET_KEY'

client = AipSpeech(APP_ID, API_KEY, SECRET_KEY)
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5. Call Speech recognition interface
In the Python script, the speech recognition function can be realized by calling the relevant methods of Baidu Intelligent Speech Interface. The following is a simple example:

def speech_to_text(audio_file):
    with open(audio_file, 'rb') as f:
        audio_data = f.read()

    result = client.asr(audio_data, 'pcm', 16000, {
        'dev_pid': 1537,
    })

    if 'result' in result:
        return result['result'][0]
    else:
        return '识别失败'
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In the above code, we first open the audio file to be recognized and read the file content. Then by calling the client.asr() method, the audio data is passed to the interface for recognition. Among them, the parameter audio_data is the audio data, pcm represents the audio format, 16000 represents the audio sampling rate, dev_pid represents the language type, 1537 means Mandarin.

6. Debugging and Testing
After completing the code writing, we can use an audio file for testing. First, save the audio file that needs to be recognized in the same directory as the Python script file. Then call the speech_to_text() method in the script, passing in the path of the audio file as a parameter:

audio_file = 'speech.wav'
result = speech_to_text(audio_file)
print(result)
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After running the script, the recognition results of the corresponding audio will be displayed on the console.

7. Summary
Through the above steps, we can easily use Python to connect with Baidu intelligent voice interface to realize the speech recognition function. Baidu's intelligent voice interface provides a wealth of functions and parameters that developers can customize according to their own needs. I hope this article will be helpful to developers who use Python to connect with Baidu intelligent voice interface.

The above is my practical experience in connecting Python and Baidu intelligent voice interface. Through practice, I gained an in-depth understanding of the use of Baidu's intelligent voice interface and successfully completed the application of speech recognition. I believe that speech recognition technology will become more mature and widely used in various industries in the future.

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