TY - JOUR

T1 - Approbation of a method for studying the reflection of emotional state in children's speech and pilot psychophysiological experimental data

AU - Lyakso, Elena

AU - Ruban, Nersisson

AU - Frolova, Olga

AU - Gorodnyi, Viktor

AU - Matveev, Yuri

PY - 2020/2/27

Y1 - 2020/2/27

N2 - The goal of the study is cross-linguistic research of 8-12 year old children's emotional speech classification by experts and automatically using the material of the Russian and Tamil languages. In the proposed project, this objective will be solved by a complex analysis of the emotional speech of informants with typical development in the age range of 8–12 years, using four emotional states “sadness, joy, anger and neutral”, to analyze what is relevant and new in connection with the lack of analogous data. Comparison of data on recognizing the emotional speech of children on the material of two languages belonging to different language groups will be made. Two approaches to emotional speech recognition are planned to use – by man and automatically, moreover, for automatic recognition, different analysis algorithms will be applied. The use of different algorithms for automated assessment of emotional states according to speech features that were previously used in analyzing a specific language is new and relevant. This will make it possible to determine their universality or specificity and, perhaps, based on them to develop an entirely new approach to analyzing emotional speech of children. The standardized approach to the collection of speech material will provide valid data on the recognition of child's emotions on the base of their speech characteristics. In this paper, we describe the methodology of our study and preliminary results of a perceptual experiment.

AB - The goal of the study is cross-linguistic research of 8-12 year old children's emotional speech classification by experts and automatically using the material of the Russian and Tamil languages. In the proposed project, this objective will be solved by a complex analysis of the emotional speech of informants with typical development in the age range of 8–12 years, using four emotional states “sadness, joy, anger and neutral”, to analyze what is relevant and new in connection with the lack of analogous data. Comparison of data on recognizing the emotional speech of children on the material of two languages belonging to different language groups will be made. Two approaches to emotional speech recognition are planned to use – by man and automatically, moreover, for automatic recognition, different analysis algorithms will be applied. The use of different algorithms for automated assessment of emotional states according to speech features that were previously used in analyzing a specific language is new and relevant. This will make it possible to determine their universality or specificity and, perhaps, based on them to develop an entirely new approach to analyzing emotional speech of children. The standardized approach to the collection of speech material will provide valid data on the recognition of child's emotions on the base of their speech characteristics. In this paper, we describe the methodology of our study and preliminary results of a perceptual experiment.

KW - child speech, cross-linguistic research, emotion classification, perception psychophysiological study, Russian and Tamil languages.

KW - Child speech

KW - cross-linguistic research

KW - emotion classification

KW - perception psychophysiological study

KW - Russian and Tamil languages

KW - Cross-linguistic research

KW - Emotion classification

KW - Perception psychophysiological study

UR - https://www.mendeley.com/catalogue/4214031d-dab5-397a-9f75-da6623119d1c/

UR - http://www.scopus.com/inward/record.url?scp=85080873779&partnerID=8YFLogxK

U2 - 10.30534/ijatcse/2020/91912020

DO - 10.30534/ijatcse/2020/91912020

M3 - Article

VL - 9

SP - 649

EP - 656

JO - International Journal of Advanced Trends in Computer Science and Engineering

JF - International Journal of Advanced Trends in Computer Science and Engineering

SN - 2278-3091

IS - 1

M1 - 91

ER -