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Automatic Classification of Volumes of Water using Swallow Sounds from Cervical Auscultation

Abstract: 

The signatures of swallowing vary depending on the volume of bolus swallowed. Among existing instrumental methods, cervical auscultation (CA) captures the acoustic signatures of the swallow sound. Although many features present in the literature can characterize volumes of swallow using CA, they require manual annotations of the different components in the sound. In this work, a rich set of acoustic features, the ComParE 2016 acoustic feature set (OS) is used to investigate whether several temporal, spectral, vocal and source features and their functionals provide cues for volume classification. Experiments are performed with CA data from 56 subjects, with dry swallow and swallows of 2ml, 5ml, and 10ml of water. Three types of classification namely, dry-vs-2ml, dry-vs-5ml and dry-vs-10ml are performed separately to analyze characteristic features. Experiments reveal that OS, which does not require annotations, performs better than the baseline features that require annotation. Within OS, the features unrelated to voice source yield a better performance than the features related to voice source. In this subset of features, MFCC, RASTA filtered audio spectrum and RMS energy are found to be consistently the top performing features across all three types of classifications.

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Paper Details

Authors:
Siddharth Subramani, Achuth Rao MV, Divya Giridhar, Prasanna Suresh Hegde, Prasanta Kumar Ghosh
Submitted On:
15 May 2020 - 1:19am
Short Link:
Type:
Presentation Slides
Event:
Presenter's Name:
Siddharth Subramani
Paper Code:
BIO-P2.12
Document Year:
2020
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Document Files

Subramani_Presentation_ICASSP_2020.pdf

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[1] Siddharth Subramani, Achuth Rao MV, Divya Giridhar, Prasanna Suresh Hegde, Prasanta Kumar Ghosh, "Automatic Classification of Volumes of Water using Swallow Sounds from Cervical Auscultation", IEEE SigPort, 2020. [Online]. Available: http://sigport.org/5303. Accessed: Sep. 26, 2020.
@article{5303-20,
url = {http://sigport.org/5303},
author = {Siddharth Subramani; Achuth Rao MV; Divya Giridhar; Prasanna Suresh Hegde; Prasanta Kumar Ghosh },
publisher = {IEEE SigPort},
title = {Automatic Classification of Volumes of Water using Swallow Sounds from Cervical Auscultation},
year = {2020} }
TY - EJOUR
T1 - Automatic Classification of Volumes of Water using Swallow Sounds from Cervical Auscultation
AU - Siddharth Subramani; Achuth Rao MV; Divya Giridhar; Prasanna Suresh Hegde; Prasanta Kumar Ghosh
PY - 2020
PB - IEEE SigPort
UR - http://sigport.org/5303
ER -
Siddharth Subramani, Achuth Rao MV, Divya Giridhar, Prasanna Suresh Hegde, Prasanta Kumar Ghosh. (2020). Automatic Classification of Volumes of Water using Swallow Sounds from Cervical Auscultation. IEEE SigPort. http://sigport.org/5303
Siddharth Subramani, Achuth Rao MV, Divya Giridhar, Prasanna Suresh Hegde, Prasanta Kumar Ghosh, 2020. Automatic Classification of Volumes of Water using Swallow Sounds from Cervical Auscultation. Available at: http://sigport.org/5303.
Siddharth Subramani, Achuth Rao MV, Divya Giridhar, Prasanna Suresh Hegde, Prasanta Kumar Ghosh. (2020). "Automatic Classification of Volumes of Water using Swallow Sounds from Cervical Auscultation." Web.
1. Siddharth Subramani, Achuth Rao MV, Divya Giridhar, Prasanna Suresh Hegde, Prasanta Kumar Ghosh. Automatic Classification of Volumes of Water using Swallow Sounds from Cervical Auscultation [Internet]. IEEE SigPort; 2020. Available from : http://sigport.org/5303