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An Investigation into Audio Features and DTW Algorithms for Infant Cry Classification

Published: 25 March 2020 Publication History

Abstract

Cry is the most common phenomenon among infants, and it has been reported that babies cry for multiple reasons. Infant cry signals are thought to convey much useful information about the physiological and pathological state of the baby. Hence, in this work we analyzed these audio signals in order to classify different reasons of cries. Cry signals were especially collected for this study including three causes, namely hunger, pain and uncertainty. Modified MFCC features besides basic acoustic features were extracted from each recording. After intergroup variance examination, nine features were selected and subjected to a novel matching process based on Dynamic Time Warping (DTW) for separating infant cries. Experiment results show that nine selected features are effective to recognize cries caused by hunger, pain and other uncertain reasons. The proposed approach for infant cry analysis will provide useful information for designing towards an automatic system for detecting physiological and pathological state of the baby

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  • (2024)Multi-modal analysis of infant cry types characterizationComputers in Biology and Medicine10.1016/j.compbiomed.2023.107626167:COnline publication date: 1-Feb-2024

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  1. An Investigation into Audio Features and DTW Algorithms for Infant Cry Classification

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    cover image ACM Other conferences
    ICBBE '19: Proceedings of the 2019 6th International Conference on Biomedical and Bioinformatics Engineering
    November 2019
    214 pages
    ISBN:9781450372992
    DOI:10.1145/3375923
    Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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    • East China Normal University

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    Association for Computing Machinery

    New York, NY, United States

    Publication History

    Published: 25 March 2020

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    Author Tags

    1. Dynamic Time Warping
    2. Feature Extraction
    3. One-way ANOVA

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    • Refereed limited

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    • Shanghai Municipal Science and Technology Major Project

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    ICBBE '19

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    • (2024)Multi-modal analysis of infant cry types characterizationComputers in Biology and Medicine10.1016/j.compbiomed.2023.107626167:COnline publication date: 1-Feb-2024

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