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.