Automatic segmentation of infant cry signals using hidden Markov models

Automatic segmentation of infant cry signals using hidden Markov models

Abstract Automatic extraction of acoustic regions of interest from recordings captured in realistic clinical environments is a necessary preprocessing step in any cry analysis system. In this study, we propose a hidden Markov model (HMM) based audio segmentation method to identify the relevant acous...

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Bibliographic Details
Main Authors: Gaurav Naithani, Jaana Kivinummi, Tuomas Virtanen, Outi Tammela, Mikko J. Peltola, Jukka M. Leppänen
Format: Article
Language:English
Published: SpringerOpen 2018-01-01
Series:EURASIP Journal on Audio, Speech, and Music Processing
Subjects:
Infant cry analysis
Acoustic analysis
Audio segmentation
Hidden Markov models
Model adaptation
Online Access:http://link.springer.com/article/10.1186/s13636-018-0124-x

Internet

http://link.springer.com/article/10.1186/s13636-018-0124-x

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