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Automatic Classification of Autistic Child Vocalisations: A Novel Database and Results

Baird, A; Amiriparian, S; Cummins, N; Alcorn, AM; Batliner, A; Pugachevskiy, S; Freitag, M; ... Schuller, B; + view all (2017) Automatic Classification of Autistic Child Vocalisations: A Novel Database and Results. In: Lacerda, Francisco, (ed.) Proceedings of Interspeech 2017. (pp. pp. 849-853). International Speech Communication Association: Stockholm, Sweden. Green open access

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Abstract

Humanoid robots have in recent years shown great promise for supporting the educational needs of children on the autism spectrum. To further improve the efficacy of such interactions, user-adaptation strategies based on the individual needs of a child are required. In this regard, the proposed study assesses the suitability of a range of speech-based classification approaches for automatic detection of autism severity according to the com- monly used Social Responsiveness Scale ™ second edition (SRS- 2). Autism is characterised by socialisation limitations including child language and communication ability. When compared to neurotypical children of the same age these can be a strong indi- cation of severity. This study introduces a novel dataset of 803 utterances recorded from 14 autistic children aged between 4 – 10 years, during Wizard-of-Oz interactions with a humanoid robot. Our results demonstrate the suitability of support vector machines (SVMs) which use acoustic feature sets from multiple Interspeech C OM P AR E challenges. We also evaluate deep spec- trum features, extracted via an image classification convolutional neural network (CNN) from the spectrogram of autistic speech instances. At best, by using SVMs on the acoustic feature sets, we achieved a UAR of 73.7 % for the proposed 3-class task.

Type: Proceedings paper
Title: Automatic Classification of Autistic Child Vocalisations: A Novel Database and Results
Event: Interspeech 2017
Location: Stockholm, Sweden
Open access status: An open access version is available from UCL Discovery
DOI: 10.21437/Interspeech.2017-730
Publisher version: http://doi.org/10.21437/Interspeech.2017-730.
Language: English
Additional information: This version is the author accepted manuscript. For information on re-use, please refer to the publisher’s terms and conditions.
Keywords: children, autism, vocal irregularities, speech classification, social responsiveness scale, SRS-2, spectral features, human-robot interaction, humanoid robotics
UCL classification: UCL
UCL > Provost and Vice Provost Offices
UCL > Provost and Vice Provost Offices > School of Education
UCL > Provost and Vice Provost Offices > School of Education > UCL Institute of Education
URI: https://discovery.ucl.ac.uk/id/eprint/10040014
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