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# coding=utf-8
# --------------------------------------------------------------------------
# Copyright (c) Microsoft Corporation. All rights reserved.
# Licensed under the MIT License. See License.txt in the project root for
# license information.
# --------------------------------------------------------------------------
"""
FILE: sample_transcribe_multiple_languages.py
DESCRIPTION:
This sample demonstrates how to transcribe an audio file with multiple language
detection using the Azure AI Transcription client. This is useful for
multilingual content.
USAGE:
python sample_transcribe_multiple_languages.py
Set the environment variables with your own values before running the sample:
1) AZURE_SPEECH_ENDPOINT - the endpoint to your Speech resource.
2) AZURE_SPEECH_API_KEY - your Speech API key.
"""
import os
def sample_transcribe_multiple_languages():
# [START transcribe_multiple_languages]
from azure.core.credentials import AzureKeyCredential
from azure.ai.transcription import TranscriptionClient
from azure.ai.transcription.models import TranscriptionContent, TranscriptionOptions
# Get configuration from environment variables
endpoint = os.environ["AZURE_SPEECH_ENDPOINT"]
api_key = os.environ["AZURE_SPEECH_API_KEY"]
# Create the transcription client
client = TranscriptionClient(endpoint=endpoint, credential=AzureKeyCredential(api_key))
# Path to your audio file with multiple languages
import pathlib
audio_file_path = pathlib.Path(__file__).parent / "assets" / "audio.wav"
# Open and read the audio file
with open(audio_file_path, "rb") as audio_file:
# Create transcription options with multiple language candidates
# The service will detect which language is being spoken
options = TranscriptionOptions(locales=["en-US", "es-ES", "fr-FR", "de-DE"]) # Multiple language candidates
# Create the request content
request_content = TranscriptionContent(definition=options, audio=audio_file)
# Transcribe the audio
result = client.transcribe(request_content)
# Print the transcription result with locale information
print("Transcription with language detection:\n")
if result.phrases:
for phrase in result.phrases:
locale = phrase.locale if hasattr(phrase, "locale") and phrase.locale else "detected"
print(f"[{locale}] {phrase.text}")
else:
print(f"Full transcription: {result.combined_phrases[0].text}")
# [END transcribe_multiple_languages]
if __name__ == "__main__":
sample_transcribe_multiple_languages()
|
