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Author: Dara Pir

Affiliation: Information Technology Program, Guttman Community College, City University of New York, New York and U.S.A.

Keyword(s): Food Likability, Acoustic Features, Group Feature Selection, Large Acoustic Feature Sets, Computational Paralinguistics.

Related Ontology Subjects/Areas/Topics: Feature Selection and Extraction ; Pattern Recognition ; Theory and Methods

Abstract: This paper presents the novel Cascaded acoustic Group and Individual Feature Selection (CGI-FS) method for automatic recognition of food likability rating addressed in the ICMI 2018 Eating Analysis and Tracking Challenge’s Likability Sub-Challenge. Employing the speech and video recordings of the iHEARu-EAT database, the Likability Sub-Challenge attempts to recognize self-reported binary labels, ‘Neutral’ and ‘Like’, assigned by subjects to food they consumed while speaking. CGI-FS uses an audio approach and performs a sequence of two feature selection operations by considering the acoustic feature space first in groups and then individually. In CGI-FS, an acoustic group feature is defined as a collection of features generated by the application of a single statistical functional to a specified set of audio low-level descriptors. We investigate the performance of CGI-FS using four different classifiers and evaluate the relevance of group features to the task. All four CGI-FS system r esults outperform the Likability Sub-Challenge baseline on iHEARu-EAT development data with the best performance achieving a 9.8% relative Unweighted Average Recall improvement over it. (More)

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Paper citation in several formats:
Pir, D. (2019). Cascaded Acoustic Group and Individual Feature Selection for Recognition of Food Likability. In Proceedings of the 8th International Conference on Pattern Recognition Applications and Methods - ICPRAM; ISBN 978-989-758-351-3; ISSN 2184-4313, SciTePress, pages 881-886. DOI: 10.5220/0007683708810886

@conference{icpram19,
author={Dara Pir.},
title={Cascaded Acoustic Group and Individual Feature Selection for Recognition of Food Likability},
booktitle={Proceedings of the 8th International Conference on Pattern Recognition Applications and Methods - ICPRAM},
year={2019},
pages={881-886},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0007683708810886},
isbn={978-989-758-351-3},
issn={2184-4313},
}

TY - CONF

JO - Proceedings of the 8th International Conference on Pattern Recognition Applications and Methods - ICPRAM
TI - Cascaded Acoustic Group and Individual Feature Selection for Recognition of Food Likability
SN - 978-989-758-351-3
IS - 2184-4313
AU - Pir, D.
PY - 2019
SP - 881
EP - 886
DO - 10.5220/0007683708810886
PB - SciTePress

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