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sonopy's Introduction

Sonopy

A simple audio feature extraction library

spectrum-image

Sonopy is a lightweight Python library used to calculate the MFCCs of an audio signal. It implements the following audio vectorization functions:

  • Power spectrogram
  • Mel spectrogram
  • Mel frequency cepstrum coefficient spectrogram

Features

  • Lightweight
  • Tiny, readable source code
  • Visualize steps in calculation

Usage

import numpy as np
from sonopy import power_spec, mel_spec, mfcc_spec, filterbanks

sr = 16000
audio = np.random.random((2 * 16000))

powers = power_spec(audio, window_stride=(100, 50), fft_size=512)
mels = mel_spec(audio, sr, window_stride=(1600, 800), fft_size=1024, num_filt=30)
mfccs = mfcc_spec(audio, sr, window_stride=(160, 80), fft_size=512, num_filt=20, num_coeffs=13)
filters = filterbanks(16000, 20, 257)  # Probably not ever useful

powers, filters, mels, mfccs = mfcc_spec(audio, sr, return_parts=True)

Installation

pip install sonopy
pip install "sonopy[example]"  # For example.py
pip install "sonopy[comparison]"  # For comparison.py

Speed Comparison

speed-chart

Param Set Audio Len Stride Window FFT Size Sample Rate Ceptral Coeffs Num Filters Loops
C 16000 0.1 0.1 2048 16000 13 20 2000
B 240000 0.05 0.05 2048 16000 13 20 200
A 480000 0.01 0.01 2048 16000 13 20 20
D 16000 0.1 0.1 512 16000 13 20 20000

Library links:

Credits

Thanks to SpeechPy for providing an example of the concrete calculations for MFCCs. Much of the calculations in this library take influence from it.

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