Discovering dimensions of perceived vocal expression in semi-structured, unscripted oral history accounts

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

Abstract

What do people hear in expressive, unprompted speech? And how can their descriptions be transformed into a representative set of dimensions of vocal expression? This paper presents a methodology for collecting user description of vocal expression, transforms the user descriptions into a set of measurable expressive dimensions, and derives a representative feature set and baseline classifiers across these dimensions. The resulting classifiers recognized the top 13 dimensions over an oral history corpus, with a maximum unweighted recall score of 80.5%

Original languageEnglish (US)
Title of host publication2017 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2017 - Proceedings
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages5695-5699
Number of pages5
ISBN (Electronic)9781509041176
DOIs
StatePublished - Jun 16 2017
Event2017 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2017 - New Orleans, United States
Duration: Mar 5 2017Mar 9 2017

Publication series

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

Other

Other2017 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2017
CountryUnited States
CityNew Orleans
Period3/5/173/9/17

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Keywords

  • Perception
  • acoustic correlates
  • oral histories
  • paralingual speech
  • unscripted speech
  • vocal expression

ASJC Scopus subject areas

  • Software
  • Signal Processing
  • Electrical and Electronic Engineering

Cite this

Pietrowicz, M., Hasegawa-Johnson, M., & Karahalios, K. (2017). Discovering dimensions of perceived vocal expression in semi-structured, unscripted oral history accounts. In 2017 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2017 - Proceedings (pp. 5695-5699). [7953247] (ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/ICASSP.2017.7953247