On the Normalization of Syllable Prominence Ratings

Research output: Contributions to collected editions/worksArticle in conference proceedingsResearchpeer-review

Standard

On the Normalization of Syllable Prominence Ratings. / Sappok, Christopher; Arnold, Denis.

Proceedings of the 6th International Conference on Speech Prosody 2012. ed. / Qiuwu Ma; Hongwei Ding; Daniel Hirst. Vol. 1 Tongji University Press, 2012. p. 314-317.

Research output: Contributions to collected editions/worksArticle in conference proceedingsResearchpeer-review

Harvard

Sappok, C & Arnold, D 2012, On the Normalization of Syllable Prominence Ratings. in Q Ma, H Ding & D Hirst (eds), Proceedings of the 6th International Conference on Speech Prosody 2012. vol. 1, Tongji University Press, pp. 314-317, 6th International Conference: Speech Prosody - ISCA Speech 2012, Shanghai, China, 22.05.12.

APA

Sappok, C., & Arnold, D. (2012). On the Normalization of Syllable Prominence Ratings. In Q. Ma, H. Ding, & D. Hirst (Eds.), Proceedings of the 6th International Conference on Speech Prosody 2012 (Vol. 1, pp. 314-317). Tongji University Press.

Vancouver

Sappok C, Arnold D. On the Normalization of Syllable Prominence Ratings. In Ma Q, Ding H, Hirst D, editors, Proceedings of the 6th International Conference on Speech Prosody 2012. Vol. 1. Tongji University Press. 2012. p. 314-317

Bibtex

@inbook{ac5fa4f3cea04f2ead848bf938bbac54,
title = "On the Normalization of Syllable Prominence Ratings",
abstract = "The instructions under which raters quantify syllable prominence perception need to be simple in order to maintain immediate reactions. This leads to noise in the rating data that can be dealt with by normalization, e.g. setting central tendency = 0 and dispersion = 1 (as in Z-score normalization). Questions arise such as: Which parameter is adequate here to capture central tendency? Which reference distribution should the normalization be based on? In this paper 16 different normalization methods are evaluated. In a perception experiment using German read speech (prose and poetry), syllable prominence ratings were collected. From the rating data 16 complete “mirror” data-sets were computed according to the 16 methods. Each mirror data-set was correlated with the same set of measures from the underlying acoustic data, focusing on raw syllable duration which is seen as a rather straightforward acoustic aspect of syllable prominence. Correlation coefficients could be raised considerably by selected methods.",
keywords = "Language Studies, Phonetik, Prosodieforschung",
author = "Christopher Sappok and Denis Arnold",
year = "2012",
language = "English",
volume = "1",
pages = "314--317",
editor = "Qiuwu Ma and Hongwei Ding and Daniel Hirst",
booktitle = "Proceedings of the 6th International Conference on Speech Prosody 2012",
publisher = "Tongji University Press",
address = "China",
note = "6th International Conference: Speech Prosody - ISCA Speech 2012 : Prosody in the real world: Understanding and approaching human prosodic performance, ISCA Speech 2012 ; Conference date: 22-05-2012 Through 25-05-2012",
url = "http://www.isle.illinois.edu/sprosig/sp2012/",

}

RIS

TY - CHAP

T1 - On the Normalization of Syllable Prominence Ratings

AU - Sappok, Christopher

AU - Arnold, Denis

N1 - Conference code: 6

PY - 2012

Y1 - 2012

N2 - The instructions under which raters quantify syllable prominence perception need to be simple in order to maintain immediate reactions. This leads to noise in the rating data that can be dealt with by normalization, e.g. setting central tendency = 0 and dispersion = 1 (as in Z-score normalization). Questions arise such as: Which parameter is adequate here to capture central tendency? Which reference distribution should the normalization be based on? In this paper 16 different normalization methods are evaluated. In a perception experiment using German read speech (prose and poetry), syllable prominence ratings were collected. From the rating data 16 complete “mirror” data-sets were computed according to the 16 methods. Each mirror data-set was correlated with the same set of measures from the underlying acoustic data, focusing on raw syllable duration which is seen as a rather straightforward acoustic aspect of syllable prominence. Correlation coefficients could be raised considerably by selected methods.

AB - The instructions under which raters quantify syllable prominence perception need to be simple in order to maintain immediate reactions. This leads to noise in the rating data that can be dealt with by normalization, e.g. setting central tendency = 0 and dispersion = 1 (as in Z-score normalization). Questions arise such as: Which parameter is adequate here to capture central tendency? Which reference distribution should the normalization be based on? In this paper 16 different normalization methods are evaluated. In a perception experiment using German read speech (prose and poetry), syllable prominence ratings were collected. From the rating data 16 complete “mirror” data-sets were computed according to the 16 methods. Each mirror data-set was correlated with the same set of measures from the underlying acoustic data, focusing on raw syllable duration which is seen as a rather straightforward acoustic aspect of syllable prominence. Correlation coefficients could be raised considerably by selected methods.

KW - Language Studies

KW - Phonetik

KW - Prosodieforschung

M3 - Article in conference proceedings

VL - 1

SP - 314

EP - 317

BT - Proceedings of the 6th International Conference on Speech Prosody 2012

A2 - Ma, Qiuwu

A2 - Ding, Hongwei

A2 - Hirst, Daniel

PB - Tongji University Press

T2 - 6th International Conference: Speech Prosody - ISCA Speech 2012

Y2 - 22 May 2012 through 25 May 2012

ER -

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