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Speech Corpus for Korean Children with Autism Spectrum Disorder: Towards Automatic Assessment Systems (2402.15539v1)

Published 23 Feb 2024 in eess.AS and cs.CL

Abstract: Despite the growing demand for digital therapeutics for children with Autism Spectrum Disorder (ASD), there is currently no speech corpus available for Korean children with ASD. This paper introduces a speech corpus specifically designed for Korean children with ASD, aiming to advance speech technologies such as pronunciation and severity evaluation. Speech recordings from speech and language evaluation sessions were transcribed, and annotated for articulatory and linguistic characteristics. Three speech and language pathologists rated these recordings for social communication severity (SCS) and pronunciation proficiency (PP) using a 3-point Likert scale. The total number of participants will be 300 for children with ASD and 50 for typically developing (TD) children. The paper also analyzes acoustic and linguistic features extracted from speech data collected and completed for annotation from 73 children with ASD and 9 TD children to investigate the characteristics of children with ASD and identify significant features that correlate with the clinical scores. The results reveal some speech and linguistic characteristics in children with ASD that differ from those in TD children or another subgroup of ASD categorized by clinical scores, demonstrating the potential for developing automatic assessment systems for SCS and PP.

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References (42)
  1. Comparing two lego robotics-based interventions for social skills training with children with asd. In 2013 IEEE RO-MAN, pages 638–643. IEEE.
  2. American Psychiatric Association. 2013. Diagnostic and statistical manual of mental disorders, 5th edition edition. American Psychiatric Association.
  3. The USC CARE corpus: child-psychologist interactions of children with autism spectrum disorders. In Interspeech 2011, pages 1497–1500. ISCA.
  4. Paul Boersma and David Weenink. 2023. Praat: doing phonetics by computer (version 6.3.10).
  5. Spontaneous-speech acoustic-prosodic features of children with autism and the interacting psychologist. In Interspeech 2012, pages 1043–1046. ISCA.
  6. Abnormal speech spectrum and increased pitch variability in young autistic children. Frontiers in Human Neuroscience, 4:237.
  7. Outcome at 7 years of children diagnosed with autism at age 2: predictive validity of assessments conducted at 2 and 3 years of age and pattern of symptom change over time. Journal of Child Psychology and Psychiatry, 46(5):500–513.
  8. Dysarthric speech database for development of QoLT software technology. In Proceedings of the Eighth International Conference on Language Resources and Evaluation (LREC’12), pages 3378–3381, Istanbul, Turkey. European Language Resources Association (ELRA).
  9. Computer-aided screening of autism spectrum disorder: Eye-tracking study using data visualization and deep learning. JMIR human factors, 8(4):e27706.
  10. Phonetic and phonological errors in children with high functioning autism and asperger syndrome. International Journal of Speech-Language Pathology, 12(1):69–76.
  11. Ignasi Clemente. 2008. Recording audio and video. The Blackwell guide to research methods in bilingualism and multilingualism, pages 177–191.
  12. Joshua John Diehl and Rhea Paul. 2012. Acoustic differences in the imitation of prosodic patterns in children with autism spectrum disorders. Research in autism spectrum disorders, 6(1):123–134.
  13. Adi-r and ados and the differential diagnosis of autism spectrum disorders: Interests, limits and openings. L’encephale, 45(5):441–448.
  14. Is voice a marker for autism spectrum disorder? a systematic review and meta-analysis. Autism Research, 10(3):384–407.
  15. Improving ASR systems for children with autism and language impairment using domain-focused DNN transfer techniques: 20th Annual Conference of the International Speech Communication Association: Crossroads of Speech and Language, INTERSPEECH 2019. Proceedings of the Annual Conference of the International Speech Communication Association, INTERSPEECH, 2019-September:11–15.
  16. Cepstral peak prominence: a more reliable measure of dysphonia. The Annals of Otology, Rhinology, and Laryngology, 112(4):324–333.
  17. Introducing parselmouth: A python interface to praat. Journal of Phonetics, 71:1–15.
  18. Assessment of Phonology and Articulation for Children (APAC). Human Brain Research & Counseling.
  19. Receptive & expressive vocabulary test (REVT). Seoul Community Rehabilitation Center.
  20. Sequenced Language Scale for Infants (SELSI). Special Education Publishing.
  21. Preschool Receptive-Expressive Language Scale (PRES). Seoul Community Rehabilitation Center.
  22. Using 2d video-based pose estimation for automated prediction of autism spectrum disorders in young children. Scientific Reports, 11(1):15069.
  23. Who Is He? Children with ASD and ADHD Take the Listener into Account in Their Production of Ambiguous Pronouns. PloS One, 10(7):e0132408.
  24. Bruce W. Lee and Jason Lee. 2023. LFTK: Handcrafted features in computational linguistics. In Proceedings of the 18th Workshop on Innovative Use of NLP for Building Educational Applications (BEA 2023), pages 1–19, Toronto, Canada. Association for Computational Linguistics.
  25. Research on construction of the korean speech corpus in patient with velopharyngeal insufficiency. Korean J Otorhinolaryngol-Head Neck Surg, 55(8):498–507.
  26. Knowledge-driven speech features for detection of korean-speaking children with autism spectrum disorder. Phonetics and Speech Sciences, 15:53–59.
  27. Language Scale for School-aged Children (LSSC). Inpsyt.
  28. Automatic classification of asd children using appearance-based features from videos. Neurocomputing, 470:40–50.
  29. Autism diagnostic observation schedule-2nd edition (ADOS-2), 2nd edition edition. Western Psychological Corporation.
  30. Perception and acoustic features of speech of children with autism spectrum disorders. In Speech and Computer, Lecture Notes in Computer Science, pages 602–612. Springer International Publishing.
  31. Joanne McCann and Sue Peppé. 2003. Prosody in autism spectrum disorders: a critical review. International Journal of Language & Communication Disorders, 38(4):325–350.
  32. librosa/librosa: 0.9.2.
  33. Soyeong Pae and Keum-Joo Kwak. 2011. Korean MacArthur-Bates Communicative Development Inventories (K M-B CDI). Mindpress.
  34. Lydia R Qualls and Blythe A Corbett. 2017. Examining the relationship between social communication on the ados and real-world reciprocal social communication in children with asd. Research in autism spectrum disorders, 33:1–9.
  35. Subtypes of language disorders in school-age children with autism. Developmental Neuropsychology, 34(1):66–84.
  36. The hypothesis of apraxia of speech in children with autism spectrum disorder. Journal of Autism and Developmental Disorders, 41(4):405–426.
  37. Maksim A. Terpilowski. 2019. scikit-posthocs: Pairwise multiple comparison tests in python. Journal of Open Source Software, 4(36):1169.
  38. Follow-up of children with autism spectrum disorders from age 2 to age 9. Autism: The International Journal of Research and Practice, 10(3):243–265.
  39. SciPy 1.0: Fundamental algorithms for scientific computing in python. Nature Methods, 17:261–272.
  40. Amy M Wetherby. 2006. Understanding and measuring social communication in children with autism spectrum disorders. Social and communication development in autism spectrum disorders: Early identification, diagnosis, and intervention, 18(3):3–34.
  41. Lesley Wolk and Christine Brennan. 2013. Phonological investigation of speech sound errors in children with autism spectrum disorders. Speech, Language and Hearing, 16(4):239–246.
  42. Global trends and hotspots in the digital therapeutics of autism spectrum disorders: a bibliometric analysis from 2002 to 2022. Frontiers in Psychiatry, 14:1126404.
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Authors (4)
  1. Seonwoo Lee (2 papers)
  2. Jihyun Mun (3 papers)
  3. Sunhee Kim (8 papers)
  4. Minhwa Chung (10 papers)
Citations (1)

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