Audio Feature Extraction Algorithms and Implementation Technologies Analysis

LIBROSA is a powerful Python audio data processing library introduced in recent years. Based on LIBROSA provided source codes, two types of feature data extraction algorithms are analyzed in detail, including MEL power spectrum and CHROMA syllable spectrums. By each algorithm, 128, 12 floating point numbers are extracted as the feature data of their corresponding spectrums. In addition, from multi perspectives of basic music theory, mathematical analysis, signal processing, computer programming and so on, deeply discusses LIBROSA library functions involved Discrete Fourier Transform (DFT), Triangular filter, Gaussian filter, and other programming technologies. The DFT algorithm, time domain window function, syllable feature data extraction, band-pass filter code analysis and other contents discussed have important reference value in data processing, deep learning and other fields of underlying model creation, source codes development and so on