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In: Proceedings of the 18th Annual Conference of the International Speech Communication Association (INTERSPEECH 2017), Stockholm, Sweden, 20\u201324 August 2017, pp. 309\u2013313. International Speech Communication Association. https:\/\/doi.org\/10.21437\/Interspeech.2017-1007.","DOI":"10.21437\/Interspeech.2017-1007"},{"issue":"6","key":"10.1016\/j.cosrev.2026.100969_bib0159","doi-asserted-by":"crossref","first-page":"498","DOI":"10.1093\/ijnp\/pyx014","article-title":"Cry, baby, cry: expression of distress as a biomarker and modulator in autism spectrum disorder","volume":"20","author":"Esposito","year":"2017","journal-title":"International Journal of Neuropsychopharmacology"},{"key":"10.1016\/j.cosrev.2026.100969_bib0160","series-title":"2013 9th Asian Control Conference (ASCC)","first-page":"1","article-title":"Using general sound descriptors for early autism detection","author":"Motlagh","year":"2013"},{"key":"10.1016\/j.cosrev.2026.100969_bib0161","series-title":"2013 IEEE International Conference on Acoustics, Speech and Signal Processing","first-page":"7567","article-title":"Very early detection of autism spectrum disorders based on acoustic analysis of 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A convolutional neural network for gaze preference detection: a potential tool for diagnostics of autism spectrum disorder in children. arXiv preprint arXiv:2007.14432. doi:10.48550\/arXiv.2007.14432."},{"key":"10.1016\/j.cosrev.2026.100969_bib0216","series-title":"Proceedings of the 3rd ACM SIGCAS Conference on Computing and Sustainable Societies","first-page":"324","article-title":"Gaze-based screening of autistic traits for adolescents and young adults using prosaic videos","author":"Ahuja","year":"2020"},{"key":"10.1016\/j.cosrev.2026.100969_bib0217","series-title":"Proceedings of the 17th International Web for All Conference","first-page":"1","article-title":"Autism detection based on eye movement sequences on the web: a scanpath trend analysis approach","author":"Eraslan","year":"2020"},{"key":"10.1016\/j.cosrev.2026.100969_bib0218","doi-asserted-by":"crossref","first-page":"994","DOI":"10.1016\/j.procs.2020.03.399","article-title":"Analysis and detection of autism spectrum 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