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process_audio_wrapper.py

Design Considerations and Enhancements

  • Synchronous Wrapper for Asynchronous Tasks: The process_audio_sync function provides a synchronous wrapper to handle the asynchronous audio processing tasks. This allows easier integration with synchronous environments while still leveraging the efficiency of asynchronous operations.
  • Comprehensive Audio Processing Pipeline: The module integrates multiple stages of audio processing, including file transformation, Voice Activity Detection (VAD), segmentation, and Signal-to-Noise Ratio (SNR) calculation, ensuring a robust and thorough audio preparation process.
  • Error Handling and Logging: The module uses loguru for detailed logging and includes exception handling to ensure graceful handling of errors during audio processing.

Module Overview

The process_audio_wrapper.py module provides a synchronous wrapper for the audio processing pipeline, which includes transforming audio files, segmenting them based on VAD, and calculating SNR for each segment. It enables synchronous execution of asynchronous tasks, simplifying its usage in environments that may not fully support asynchronous programming.

Key Libraries and Dependencies

  • asyncio: Used for managing asynchronous tasks. The module creates an asynchronous event loop to handle the non-blocking processing of audio files.

Functions

process_audio_sync

The process_audio_sync function is a synchronous wrapper that runs the asynchronous process_audio pipeline. It performs audio processing tasks such as transforming files, applying Voice Activity Detection (VAD), creating segments, and calculating the Signal-to-Noise Ratio (SNR) for each audio segment.

Function: process_audio_sync(worker_name: str, source_file_path: Path, model_for_vad: Path, output_dir: Path) -> None

This function executes the audio processing pipeline synchronously by creating an event loop and running the asynchronous tasks within that loop. It handles the following key audio processing steps:

  1. Transforms the source file to WAV format.
  2. Creates Voice Activity Detection (VAD) segments from the audio file.
  3. Segments the audio based on VAD.
  4. Calculates the Signal-to-Noise Ratio (SNR) for each segment.
  • How it Works:
    • Transformation: The audio file is transformed into WAV format if necessary.
    • VAD Processing: The file undergoes Voice Activity Detection (VAD) to identify active speech segments.
    • Segmentation: The audio is segmented based on the VAD results.
    • SNR Calculation: For each audio segment, the Signal-to-Noise Ratio (SNR) is calculated, providing a measure of audio quality.
    • Asynchronous Execution: All of these steps are run asynchronously within the runner() function, but the process_audio_sync() function wraps this in a synchronous interface for easier integration with other synchronous code.
def process_audio_sync(worker_name: str, source_file_path: Path, model_for_vad: Path, output_dir: Path) -> None:
    """
    Synchronous wrapper to run the asynchronous process_audio method.
    
    Args:
        worker_name (str): Identifier for the worker.
        source_file_path (Path): Path to the source audio file to be processed.
        model_for_vad (Path): Path to the Voice Activity Detection (VAD) model used for segmenting the audio.
        output_dir (Path): Directory where processed audio files and segments will be saved.

    Returns:
        None
    """

Inner Function: runner() -> None

The runner() function is the core asynchronous function that performs the audio processing tasks. It interacts with the AudioProcessor class to process the audio file in stages: transforming, segmenting, and calculating SNR.

  • Audio Transformation: Converts the audio file to WAV format if needed.

  • VAD Processing: Detects voice activity in the audio file and generates corresponding segments.

  • Segmentation: Divides the audio file into segments based on the VAD results.

  • SNR Calculation: Computes the Signal-to-Noise Ratio for each segment.

  • Error Handling: Any exceptions that occur during the processing steps are caught and logged.

async def runner() -> None:
    """
    Asynchronous function that processes audio files.

    This function performs the following steps:
    1. Transforms the source file to WAV format.
    2. Creates Voice Activity Detection (VAD) segments from the audio file.
    3. Segments the audio based on VAD.
    4. Calculates Signal-to-Noise Ratio (SNR) for each segment.

    Raises:
        Exception: If an error occurs during the audio processing.

    Returns:
        None
    """

Usage Example

The following example demonstrates how to use the process_audio_sync function to process an audio file synchronously, with logging and output handled in a specified directory.

from pathlib import Path
from process_audio_wrapper import process_audio_sync

# Example values
worker_name = "worker_1"
source_file = Path("path/to/audio/file.wav")
vad_model = Path("path/to/vad/model")
output_directory = Path("path/to/output")

# Synchronously process the audio file
process_audio_sync(worker_name, source_file, vad_model, output_directory)

Key Steps in the Example:

  1. Define Worker and Paths: Set up identifiers, paths to the audio file, VAD model, and output directory.

  2. Run process_audio_sync:

    • The function synchronously processes the audio file, transforming it to WAV format, applying VAD, segmenting it, and calculating SNR for each segment. The processed data is saved in the specified output directory.

This example shows how to integrate the synchronous audio processing wrapper in an application where asynchronous tasks are managed in a blocking environment.