Teach you how to use Python to connect to Huawei Cloud interface to implement audio transcription and synthesis functions

Teach you how to use Python to connect to Huawei Cloud interface to implement audio transcription and synthesis functions

Introduction:
With the development of artificial intelligence technology, speech synthesis and speech recognition have become many application fields A must-have feature. As a developer, we can use Python language to connect to the Huawei Cloud interface to implement audio transcription and synthesis functions. This article will introduce how to use Python to connect to Huawei Cloud interface to realize the transcription and speech synthesis functions of audio files.

1. Register a Huawei Cloud account
To use Huawei Cloud's voice service, you first need to register an account on Huawei Cloud and create a speech recognition and synthesis service instance.

2. Install dependent libraries
To connect to Huawei Cloud in Python, you need to use the Python SDK. We first need to install the corresponding libraries:

pip install huaweicloud-sdkcore
pip install huaweicloud-sdkasr
pip install huaweicloud-sdktts
pip install pydub

huaweicloud-sdkcore is the Python SDK core of Huawei Cloud library, while huaweicloud-sdkasr and huaweicloud-sdktts are Python SDKs for speech recognition and speech synthesis.

Pydub is a Python library for processing audio files. We will use it to process audio file formats.

3. Speech Transcription
First, we need to upload the audio files to be transcribed to the Huawei Cloud Object Storage OBS service. Then connect to Huawei Cloud's voice service through the Python SDK and call the speech recognition interface for transcription.

The following is a sample code to implement the function of transcribing audio files into text:

from huaweicloud-sdkcore.auth.credentials import GlobalCredentials
from huaweicloud-sdkasr.v1.asr_client import AsrClient

ak = 'your access key'
sk = 'your secret key'
region = 'your region'
endpoint = 'https://asr.myhuaweicloud.com'

def recognize(file_path):
    creds = GlobalCredentials().with_aksk(ak, sk)
    client = AsrClient.new_builder().with_credentials(creds).with_endpoint(endpoint).build()

    with open(file_path, 'rb') as f:
        file_data = f.read()

    try:
        resp = client.recognize(file_data)
        result = resp.result
        return result
    except Exception as e:
        print("Recognize failed: ", e)

In this example, we first need to set the Access Key and Secret created on Huawei Cloud Key, and the area where it is located.

Then use the recognize method of AsrClient to read and convert the audio file into a byte stream and send it to the speech recognition interface of Huawei Cloud. After the interface is called successfully, the audio transcription result will be returned.

4. Speech synthesis
Let’s realize the function of speech synthesis. Similarly, we need to upload the text to be synthesized to the Huawei Cloud Object Storage OBS service. Then connect to Huawei Cloud's voice service through Python SDK and call the speech synthesis interface for synthesis.

from huaweicloud-sdkcore.auth.credentials import GlobalCredentials
from huaweicloud-sdktts.v1.tts_client import TtsClient

ak = 'your access key'
sk = 'your secret key'
region = 'your region'
endpoint = 'https://tts.myhuaweicloud.com'

def text_to_speech(text, file_path):
    creds = GlobalCredentials().with_aksk(ak, sk)
    client = TtsClient.new_builder().with_credentials(creds).with_endpoint(endpoint).build()

    try:
        resp = client.create_notify(body= {
            "text": text,
            "voice_name": "xiaoyan",
            "sample_rate": 16,
            "volume": 0,
            "speed": 0,
            "pitch": 0,
            "format": "mp3"
        })
        body = resp.result

        download_link = body['download_link']
        urllib.request.urlretrieve(download_link, file_path)
        print('Speech synthesis completed!')
    except Exception as e:
        print("Text to speech failed: ", e)

In this example, we also need to set the Access Key and Secret Key created on Huawei Cloud, as well as the region where they are located.

Then send a synthetic request through the create_notify method of TtsClient. We need to provide relevant information such as text to be synthesized, sound style, audio parameters, etc. After the interface is called successfully, Huawei Cloud will generate a synthesized audio file and provide a download link.

We can use the urlretrieve method in the urllib library to download the audio file locally and save it in mp3 format.

Conclusion:
Through the above steps, we can see how to use Python to connect to the Huawei Cloud interface to implement audio transcription and synthesis functions. Using Huawei Cloud's powerful voice services, we can quickly implement speech recognition and speech synthesis functions in various application scenarios.

It should be noted that this article is only a sample code, and some parameters need to be set according to your actual situation. In actual applications, the functions can be further optimized and expanded according to your own needs. I hope this article will be helpful to you. Welcome to visit the official Huawei Cloud website to learn more about voice services.

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