Teach you how to use Python to connect to the Huawei Cloud interface to implement the audio transcription function
In modern society, the widespread application of speech recognition technology has become a trend in various fields. People often need to convert audio files into text for further analysis and processing. Huawei Cloud provides a powerful audio transcription service. This article will teach you how to use Python to connect to the Huawei Cloud interface to implement the audio transcription function.
Step 1: Register a Huawei Cloud account and create a project
First, you need to register a Huawei Cloud account and create a new project. Log in to the Huawei Cloud console, create a new Access Key, and write down the Access Key ID and Access Key Secret, which will be used in subsequent steps.
Step 2: Install the necessary Python libraries
Before connecting to the Huawei Cloud interface, you need to install the Python HTTP library and the Alibaba Cloud SDK locally. Open a terminal or command line window and execute the following command to install the required libraries:
pip install requests pip install huaweicloud-sdk-core pip install huaweicloud-sdk-asr
Step 3: Write the transcoding code
Next, write the code in Python, connect to the Huawei Cloud interface, and Take advantage of the audio transcription services they offer. First, import the necessary libraries:
import requests from huaweicloudSdkcore.auth.credentials import GlobalCredentials from huaweicloudSdkcore.region.region import Region from huaweicloudSdkasr.v1 import asrClient from huaweicloudSdkasr.v1.region.region import Region from huaweicloudSdkcore.exceptions import exceptions
Next, define some parameters required for the Huawei Cloud interface, including the Access Key ID and Access Key Secret you recorded in step one, the audio file path, and the audio format:
ak = "your_access_key_id" sk = "your_access_key_secret" project_id = "your_project_id" region = "cn-north-1" audio_file = "/path/to/your/audio/file.wav"
Then, create a client for the Huawei Cloud interface:
credentials = GlobalCredentials.get_credentials(ak, sk) asr_client = asrClient.AsrClient.new_builder() .with_http_config(http_proxy=None, https_proxy=None, no_proxy=None) .with_credentials(credentials) .with_default_headers({"x-language": "zh-cn"}) .with_region(Region(region)) .build()
Next, read the binary data of the audio file and convert it to Base64 encoding:
with open(audio_file, mode='rb') as file: audio_data = file.read() audio_base64 = base64.b64encode(audio_data).decode()
Finally, call the Huawei Cloud interface, pass the audio data to the interface for transcription, and obtain the transcription result:
request_body = { "data": audio_base64, "encode_type": "wav", "sample_rate": 16000 } response = asr_client.create_task(request_body=request_body, project_id=project_id).result task_id = response.body["result"]["task_id"] while response.body["status"] != "done": response = asr_client.get_task_result(task_id=task_id, project_id=project_id).result time.sleep(1) result = response.body["result"]["result"]
At this point, you have successfully completed the audio transcription function. Print out the transcription result or save it as a text file:
print(result) with open("/path/to/your/output/file.txt", mode='w', encoding='utf-8') as file: file.write(result)
The above is a complete code example of using Python to connect to the Huawei Cloud interface to implement the audio transcription function.
Summary:
Through the introduction and code examples of this article, you have learned how to use Python to connect to the Huawei Cloud interface and implement the audio file transcoding function. Audio transcription has important applications in many scenarios, such as speech recognition, speech translation, etc. Using the efficient and accurate audio transcription service provided by Huawei Cloud can greatly improve work efficiency and accuracy. I hope this article is helpful to you, and I wish you can successfully apply audio transcription technology in actual projects!
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