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Voice Features as the Diagnostic Marker of Autism. / Lyakso, Elena ; Frolova, Olga ; Matveev , Yuri .

In: International Journal of Psychological and Behavioral Sciences , Vol. 16, No. 7, 2022, p. 377-382.

Research output: Contribution to journalArticlepeer-review

Harvard

Lyakso, E, Frolova, O & Matveev , Y 2022, 'Voice Features as the Diagnostic Marker of Autism', International Journal of Psychological and Behavioral Sciences , vol. 16, no. 7, pp. 377-382.

APA

Lyakso, E., Frolova, O., & Matveev , Y. (2022). Voice Features as the Diagnostic Marker of Autism. International Journal of Psychological and Behavioral Sciences , 16(7), 377-382.

Vancouver

Lyakso E, Frolova O, Matveev Y. Voice Features as the Diagnostic Marker of Autism. International Journal of Psychological and Behavioral Sciences . 2022;16(7):377-382.

Author

Lyakso, Elena ; Frolova, Olga ; Matveev , Yuri . / Voice Features as the Diagnostic Marker of Autism. In: International Journal of Psychological and Behavioral Sciences . 2022 ; Vol. 16, No. 7. pp. 377-382.

BibTeX

@article{379223d5053d4744ad895ced9d18ac79,
title = "Voice Features as the Diagnostic Marker of Autism",
abstract = "The aim of the study is to determine the acoustic features of voice and speech of children with autism spectrum disorders (ASD) as a possible additional diagnostic criterion. The participants in the study were 95 children with ASD aged 5-16 years, 150 typically development (TD) children, and 103 adults – listening to children{\textquoteright}s speech samples. Three types of experimental methods for speech analysis were performed: spectrographic, perceptual by listeners, and automatic recognition. In the speech of children with ASD, the pitch values, pitch range, values of frequency and intensity of the third formant (emotional) leading to the “atypical” spectrogram of vowels are higher than corresponding parameters in the speech of TD children. High values of vowel articulation index (VAI) are specific for ASD children{\textquoteright}s speech signals. These acoustic features can be considered as diagnostic marker of autism. The ability of humans and automatic recognition of the psychoneurological state of children via their speech is determined.",
keywords = "autism spectrum disorders, biomarker of autism, child speech, voice features",
author = "Elena Lyakso and Olga Frolova and Yuri Matveev",
year = "2022",
language = "English",
volume = "16",
pages = "377--382",
journal = "World Academy of Science, Engineering and Technology",
issn = "1307-6892",
publisher = "World Academy of Science Engineering and Technology",
number = "7",

}

RIS

TY - JOUR

T1 - Voice Features as the Diagnostic Marker of Autism

AU - Lyakso, Elena

AU - Frolova, Olga

AU - Matveev , Yuri

PY - 2022

Y1 - 2022

N2 - The aim of the study is to determine the acoustic features of voice and speech of children with autism spectrum disorders (ASD) as a possible additional diagnostic criterion. The participants in the study were 95 children with ASD aged 5-16 years, 150 typically development (TD) children, and 103 adults – listening to children’s speech samples. Three types of experimental methods for speech analysis were performed: spectrographic, perceptual by listeners, and automatic recognition. In the speech of children with ASD, the pitch values, pitch range, values of frequency and intensity of the third formant (emotional) leading to the “atypical” spectrogram of vowels are higher than corresponding parameters in the speech of TD children. High values of vowel articulation index (VAI) are specific for ASD children’s speech signals. These acoustic features can be considered as diagnostic marker of autism. The ability of humans and automatic recognition of the psychoneurological state of children via their speech is determined.

AB - The aim of the study is to determine the acoustic features of voice and speech of children with autism spectrum disorders (ASD) as a possible additional diagnostic criterion. The participants in the study were 95 children with ASD aged 5-16 years, 150 typically development (TD) children, and 103 adults – listening to children’s speech samples. Three types of experimental methods for speech analysis were performed: spectrographic, perceptual by listeners, and automatic recognition. In the speech of children with ASD, the pitch values, pitch range, values of frequency and intensity of the third formant (emotional) leading to the “atypical” spectrogram of vowels are higher than corresponding parameters in the speech of TD children. High values of vowel articulation index (VAI) are specific for ASD children’s speech signals. These acoustic features can be considered as diagnostic marker of autism. The ability of humans and automatic recognition of the psychoneurological state of children via their speech is determined.

KW - autism spectrum disorders

KW - biomarker of autism

KW - child speech

KW - voice features

UR - https://publications.waset.org/10012604/voice-features-as-the-diagnostic-marker-of-autism

M3 - Article

VL - 16

SP - 377

EP - 382

JO - World Academy of Science, Engineering and Technology

JF - World Academy of Science, Engineering and Technology

SN - 1307-6892

IS - 7

ER -

ID: 100863302