Dimensional Analysis of Laughter in Female Conversational Speech

Mary Pietrowicz, Carla Agurto, Jonah Casebeer, Mark Allan Hasegawa-Johnson, Kyratso George Karahalios, Guillermo Cecchi

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

How do people hear laughter in expressive, unprompted speech What is the range of expressivity and function of laughter in this speech, and how can laughter inform the recognition of higher-level expressive dimensions in a corpus This paper presents a scalable method for collecting natural human description of laughter, transforming the description to a vector of quantifiable laughter dimensions, and deriving baseline classifiers for the different dimensions of expressive laughter. Then, it explores the impact of leveraging nuances of laughter in the recognition of higher-level, general expressive dimensions, discovered in the same way, such as genuine happiness, sarcasm, nervous reflection, and more. The performance of the low-level laughter classifiers is presented, along with the performance of the high-level laughter-aware and laughter-unaware classifiers.

Original languageEnglish (US)
Title of host publication2019 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2019 - Proceedings
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages6600-6604
Number of pages5
ISBN (Electronic)9781479981311
DOIs
StatePublished - May 2019
Event44th IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2019 - Brighton, United Kingdom
Duration: May 12 2019May 17 2019

Publication series

NameICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings
Volume2019-May
ISSN (Print)1520-6149

Conference

Conference44th IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2019
CountryUnited Kingdom
CityBrighton
Period5/12/195/17/19

Fingerprint

Classifiers

Keywords

  • dimensional analysis
  • latent semantic analysis
  • laughter
  • perception
  • vocal expression

ASJC Scopus subject areas

  • Software
  • Signal Processing
  • Electrical and Electronic Engineering

Cite this

Pietrowicz, M., Agurto, C., Casebeer, J., Hasegawa-Johnson, M. A., Karahalios, K. G., & Cecchi, G. (2019). Dimensional Analysis of Laughter in Female Conversational Speech. In 2019 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2019 - Proceedings (pp. 6600-6604). [8683566] (ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings; Vol. 2019-May). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/ICASSP.2019.8683566

Dimensional Analysis of Laughter in Female Conversational Speech. / Pietrowicz, Mary; Agurto, Carla; Casebeer, Jonah; Hasegawa-Johnson, Mark Allan; Karahalios, Kyratso George; Cecchi, Guillermo.

2019 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2019 - Proceedings. Institute of Electrical and Electronics Engineers Inc., 2019. p. 6600-6604 8683566 (ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings; Vol. 2019-May).

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Pietrowicz, M, Agurto, C, Casebeer, J, Hasegawa-Johnson, MA, Karahalios, KG & Cecchi, G 2019, Dimensional Analysis of Laughter in Female Conversational Speech. in 2019 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2019 - Proceedings., 8683566, ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings, vol. 2019-May, Institute of Electrical and Electronics Engineers Inc., pp. 6600-6604, 44th IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2019, Brighton, United Kingdom, 5/12/19. https://doi.org/10.1109/ICASSP.2019.8683566
Pietrowicz M, Agurto C, Casebeer J, Hasegawa-Johnson MA, Karahalios KG, Cecchi G. Dimensional Analysis of Laughter in Female Conversational Speech. In 2019 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2019 - Proceedings. Institute of Electrical and Electronics Engineers Inc. 2019. p. 6600-6604. 8683566. (ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings). https://doi.org/10.1109/ICASSP.2019.8683566
Pietrowicz, Mary ; Agurto, Carla ; Casebeer, Jonah ; Hasegawa-Johnson, Mark Allan ; Karahalios, Kyratso George ; Cecchi, Guillermo. / Dimensional Analysis of Laughter in Female Conversational Speech. 2019 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2019 - Proceedings. Institute of Electrical and Electronics Engineers Inc., 2019. pp. 6600-6604 (ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings).
@inproceedings{af32245e24cd4b5697fa3845360377c4,
title = "Dimensional Analysis of Laughter in Female Conversational Speech",
abstract = "How do people hear laughter in expressive, unprompted speech What is the range of expressivity and function of laughter in this speech, and how can laughter inform the recognition of higher-level expressive dimensions in a corpus This paper presents a scalable method for collecting natural human description of laughter, transforming the description to a vector of quantifiable laughter dimensions, and deriving baseline classifiers for the different dimensions of expressive laughter. Then, it explores the impact of leveraging nuances of laughter in the recognition of higher-level, general expressive dimensions, discovered in the same way, such as genuine happiness, sarcasm, nervous reflection, and more. The performance of the low-level laughter classifiers is presented, along with the performance of the high-level laughter-aware and laughter-unaware classifiers.",
keywords = "dimensional analysis, latent semantic analysis, laughter, perception, vocal expression",
author = "Mary Pietrowicz and Carla Agurto and Jonah Casebeer and Hasegawa-Johnson, {Mark Allan} and Karahalios, {Kyratso George} and Guillermo Cecchi",
year = "2019",
month = "5",
doi = "10.1109/ICASSP.2019.8683566",
language = "English (US)",
series = "ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
pages = "6600--6604",
booktitle = "2019 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2019 - Proceedings",
address = "United States",

}

TY - GEN

T1 - Dimensional Analysis of Laughter in Female Conversational Speech

AU - Pietrowicz, Mary

AU - Agurto, Carla

AU - Casebeer, Jonah

AU - Hasegawa-Johnson, Mark Allan

AU - Karahalios, Kyratso George

AU - Cecchi, Guillermo

PY - 2019/5

Y1 - 2019/5

N2 - How do people hear laughter in expressive, unprompted speech What is the range of expressivity and function of laughter in this speech, and how can laughter inform the recognition of higher-level expressive dimensions in a corpus This paper presents a scalable method for collecting natural human description of laughter, transforming the description to a vector of quantifiable laughter dimensions, and deriving baseline classifiers for the different dimensions of expressive laughter. Then, it explores the impact of leveraging nuances of laughter in the recognition of higher-level, general expressive dimensions, discovered in the same way, such as genuine happiness, sarcasm, nervous reflection, and more. The performance of the low-level laughter classifiers is presented, along with the performance of the high-level laughter-aware and laughter-unaware classifiers.

AB - How do people hear laughter in expressive, unprompted speech What is the range of expressivity and function of laughter in this speech, and how can laughter inform the recognition of higher-level expressive dimensions in a corpus This paper presents a scalable method for collecting natural human description of laughter, transforming the description to a vector of quantifiable laughter dimensions, and deriving baseline classifiers for the different dimensions of expressive laughter. Then, it explores the impact of leveraging nuances of laughter in the recognition of higher-level, general expressive dimensions, discovered in the same way, such as genuine happiness, sarcasm, nervous reflection, and more. The performance of the low-level laughter classifiers is presented, along with the performance of the high-level laughter-aware and laughter-unaware classifiers.

KW - dimensional analysis

KW - latent semantic analysis

KW - laughter

KW - perception

KW - vocal expression

UR - http://www.scopus.com/inward/record.url?scp=85068989942&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=85068989942&partnerID=8YFLogxK

U2 - 10.1109/ICASSP.2019.8683566

DO - 10.1109/ICASSP.2019.8683566

M3 - Conference contribution

AN - SCOPUS:85068989942

T3 - ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings

SP - 6600

EP - 6604

BT - 2019 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2019 - Proceedings

PB - Institute of Electrical and Electronics Engineers Inc.

ER -