Feature trajectory dynamic time warping for clustering of speech segments

Feature trajectory dynamic time warping for clustering of speech segments

Abstract Dynamic time warping (DTW) can be used to compute the similarity between two sequences of generally differing length. We propose a modification to DTW that performs individual and independent pairwise alignment of feature trajectories. The modified technique, termed feature trajectory dynam...

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Bibliographic Details
Main Authors: Lerato Lerato, Thomas Niesler
Format: Article
Language:English
Published: SpringerOpen 2019-04-01
Series:EURASIP Journal on Audio, Speech, and Music Processing
Subjects:
Dynamic time warping (DTW)
Feature trajectory
Speech segments
Agglomerative hierarchical clustering
Online Access:http://link.springer.com/article/10.1186/s13636-019-0149-9

Internet

http://link.springer.com/article/10.1186/s13636-019-0149-9

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