Audio Alignment and Temporal Modeling
Abstract
This chapter focuses on audio analysis methods that take into account the temporal evolution of the audio phenomena. This is done by preserving the short-term nature of the feature sequences, in order to either create methods that align two feature sequences or build temporal audio representations using Hidden Markov Models.
Keywords
Sequence alignment
Template matching
Dynamic time warping
DTW
Cost grid
Sakoe-Chiba
Itakura
Smith-Waterman
Hidden Markov Model
HMM
Baum-Welch
Viterbi algorithm
Trellis diagramn
Mixture of Gaussians
This chapter presents several methods that take into account the temporal evolution of the audio phenomena. In other words, we are no longer interested in computing ...
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