Literature DB >> 7608410

Analysis of the glottal excitation of emotionally styled and stressed speech.

K E Cummings1, M A Clements.   

Abstract

The problems of automatic recognition of and synthesis of multistyle speech have become important topics of research in recent years. This paper reports an extensive investigation of the variations that occur in the glottal excitation of eleven commonly encountered speech styles. Glottal waveforms were extracted from utterances of non-nasalized vowels for two speakers for each of the eleven speaking styles. The extracted waveforms were parametrized into four duration-related and two slope-related values. Using these six parameters, the glottal waveforms from the eleven styles of speech were analyzed both qualitatively and quantitatively. The glottal waveforms from each style speech were analyzed both qualitatively and quantitatively. The glottal waveforms from each style of speech have been shown to be significantly and identifiably different from all other styles, thereby confirming the importance of the glottal waveform in conveying speech style information and in causing speech waveform variations. The degree of variation in styled glottal waveforms has been shown to be consistent when trained on one speaker and compared with another.

Mesh:

Year:  1995        PMID: 7608410     DOI: 10.1121/1.413664

Source DB:  PubMed          Journal:  J Acoust Soc Am        ISSN: 0001-4966            Impact factor:   1.840


  4 in total

1.  CREMA-D: Crowd-sourced Emotional Multimodal Actors Dataset.

Authors:  Houwei Cao; David G Cooper; Michael K Keutmann; Ruben C Gur; Ani Nenkova; Ragini Verma
Journal:  IEEE Trans Affect Comput       Date:  2014 Oct-Dec       Impact factor: 10.506

2.  A Moan of Pleasure Should Be Breathy: The Effect of Voice Quality on the Meaning of Human Nonverbal Vocalizations.

Authors:  Andrey Anikin
Journal:  Phonetica       Date:  2020-01-21       Impact factor: 1.759

3.  Particle swarm optimization based feature enhancement and feature selection for improved emotion recognition in speech and glottal signals.

Authors:  Hariharan Muthusamy; Kemal Polat; Sazali Yaacob
Journal:  PLoS One       Date:  2015-03-23       Impact factor: 3.240

4.  Effects of Data Augmentations on Speech Emotion Recognition.

Authors:  Bagus Tris Atmaja; Akira Sasou
Journal:  Sensors (Basel)       Date:  2022-08-09       Impact factor: 3.847

  4 in total

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