Comprehensive learning notes on Hidden Markov Models, covering the three fundamental algorithms — Forward, Viterbi, and Baum-Welch — with intuitive explanations and mathematical derivations.

A deep dive into DTW's core algorithm and mathematical framework, using sight-singing as a case study to explain how the choice of feature frames — MFCC, Chroma, or F0 — fundamentally determines alignment quality.