Free Online Course: Extracting Information From Music Signals provided by Kadenze is a comprehensive online course. The course is taught in English and is free of charge. Upon completion of the course, you can receive an e-certificate from Kadenze. Extracting Information From Music Signals is taught by George Tzanetakis.
The course introduces audio signal processing concepts motivated by examples from MIR research. More specifically students will learn about spectral analysis and time-frequency representations in general, monophonic pitch estimation, audio feature extraction, beat tracking, and tempo estimation.
Session 1: Overview And Introduction To DSP
In this session, we will cover Phasors, Sinusoids, and Complex Numbers. Session 2: Time-Frequency Representations
In This session, we will learn about Sampling, Quantization, RMS, and Loudness. We will also cover DFT, Hilbert Spaces, and Spectrograms. Session 3: Monophonic Pitch Analysis/Autocorrelation
Pitch vs Fundamental Frequency, Time-domain, Frequency-domain, Perceptual Models, Overview of applications (Query-by-Humming, Auto-tunining) will be covered in this session. Session 4: Audio Feature Extraction
We will go over Spectral Features, Mel-Frequency Cepstral Coefficients, temporal aggregation, chroma and pitch profiles. Session 5: Rhythm Analysis
This session is about Tempo estimation, beat tracking, drum transcription, pattern detection.
