auparse_normalize_how - Linux

Overview

auparse_normalize_how is a tool for normalizing audio data to improve its consistency and comparability. It can be used to enhance the performance of audio analysis and machine learning tasks.

Syntax

auparse_normalize_how [OPTIONS] <INPUT_WAV_FILE> <OUTPUT_WAV_FILE>

Options/Flags

  • -m, –method: Normalization method to apply. Choose from:
    • peak: Normalize to the peak amplitude
    • max_rms: Normalize to the maximum RMS amplitude
    • desired_rms: Normalize to a desired RMS amplitude (provide with -a)
    • range: Normalize to a specific amplitude range (provide with -r)
    • match: Normalize to match the characteristics of another audio file (provide with -n)
  • -a, –amplitude: Desired RMS amplitude for -m desired_rms. Default: -20 dBFS.
  • -r, –range: Amplitude range for -m range. Provide as a minimum and maximum separated by a comma (e.g., -5,-1).
  • -n, –match: Reference audio file for -m match.
  • -h, –help: Display help and exit.

Examples

  • Normalize audio to peak amplitude:
auparse_normalize_how -m peak input.wav output.wav
  • Normalize audio to maximum RMS amplitude:
auparse_normalize_how -m max_rms input.wav output.wav
  • Normalize audio to -10 dBFS RMS amplitude:
auparse_normalize_how -m desired_rms -a -10 input.wav output.wav
  • Normalize audio to a range of -10 to -5 dBFS:
auparse_normalize_how -m range -r -10,-5 input.wav output.wav
  • Normalize audio to match the amplitude characteristics of reference.wav:
auparse_normalize_how -m match -n reference.wav input.wav output.wav

Common Issues

  • Ensure that the input and output WAV files are valid audio format.
  • If the -m desired_rms method is used, the provided amplitude should be within a reasonable range (-80 to 0 dBFS).
  • If the -m range method is used, the minimum amplitude should be less than the maximum amplitude.

Integration

  • Audio Analysis: Normalize audio before feature extraction to improve the accuracy and consistency of analysis results.
  • Machine Learning: Normalize audio before training or testing models to ensure that the data is well-distributed and suitable for modeling tasks.
  • Data Preprocessing: Normalize audio as part of a data preprocessing pipeline for various applications, such as speech recognition or sound event detection.

Related Commands

  • normalize_audio: A similar tool for normalizing audio using ffmpeg.
  • sox: A versatile audio editing and processing tool that also includes normalization capabilities.