Lord C, Elsabbagh M, Baird G, Veenstra-Vanderweele J. Autism spectrum dysfunction. Lancet. 2018;392:508–20.
Gabbay-Dizdar N, Ilan M, Meiri G, Faroy M, Michaelovski A, Flusser H, et al. Early prognosis of autism locally is related to marked enchancment in social signs inside 1–2 years. Autism. 2022;26:1353–63.
Tager-Flusberg H, Kasari C. Minimally verbal school-aged youngsters with autism spectrum dysfunction: the uncared for finish of the spectrum. Autism Res. 2013;6:468–78.
Salem AC, MacFarlane H, Adams JR, Lawley GO, Dolata JK, Bedrick S, et al. Evaluating atypical language in autism utilizing automated language measures. Sci Rep. 2021;11:10968 https://doi.org/10.1038/S41598-021-90304-5.
Chi NA, Washington P, Kline A, Husic A, Hou C, He C, et al. Classifying autism from crowdsourced semistructured speech recordings: machine studying mannequin comparability examine. JMIR Pediatr Father or mother. 2022;5:e35406.
Mostek J. Cognitive improvement and language acquisition in autistic youngsters. Sci Insig. 2022;41:719–24.
Loukusa S. Autism spectrum dysfunction. In: Cummings L, editors. Handbook of pragmatic language issues. Cham: Springer Worldwide Publishing; 2021, pp. 45–78.
Bonneh YS, Levanon Y, Dean-Pardo O, Lossos L, Adini Y. Irregular speech spectrum and elevated pitch variability in younger autistic youngsters. Entrance Hum Neurosci. 2011;4:237.
Asghari SZ, Farashi S, Bashirian S, Jenabi E. Distinctive prosodic options of individuals with autism spectrum dysfunction: a scientific overview and meta-analysis examine. Sci Rep. 2021;11:23093.
Oller DK, Niyogi P, Grey S, Richards JA, Gilkerson J, Xu D, et al. Automated vocal evaluation of naturalistic recordings from youngsters with autism, language delay, and typical improvement. Proc Natl Acad Sci USA. 2010;107:13354–9.
Moffitt JM, Ahn YA, Custode S, Tao Y, Mathew E, Parlade M, et al. Goal measurement of vocalizations within the evaluation of autism spectrum dysfunction signs in preschool age youngsters. Autism Res. 2022;15:1665–74.
Ferguson EF, Nahmias AS, Crabbe S, Liu T, Mandell DS, Parish-Morris J. Social language alternatives for preschoolers with autism: Insights from audio recordings in city school rooms. Autism. 2020;24:1232–45.
Warren SF, Gilkerson J, Richards JA, Oller DK, Xu D, Yapanel U, et al. What automated vocal evaluation reveals concerning the vocal manufacturing and language studying surroundings of younger youngsters with autism. J Autism Dev Disord. 2010;40:555–69.
Warlaumont AS, Richards JA, Gilkerson J, Oller DK. A social suggestions loop for speech improvement and its discount in autism. Psychol Sci. 2014;25:1314–24.
Plumb AM, Wetherby AM. Vocalization improvement in toddlers with autism spectrum dysfunction. J Speech Lang Hear Res. 2013;56:721–34.
Tenenbaum EJ, Carpenter KL, Sabatos‐DeVito M, Hashemi J, Vermeer S, Sapiro G, et al. A six‐minute measure of vocalizations in toddlers with autism spectrum dysfunction. Autism Res. 2020;13:1373–82.
Pokorny FB, Schuller BW, Marschik PB, Brueckner R, Nyström P, Cummins N, et al. Earlier identification of youngsters with autism spectrum dysfunction: an automated vocalisation-based method. Proceedings of the annual convention of the worldwide speech communication affiliation. Proc. Interspeech. 2017;309–13. https://doi.org/10.21437/Interspeech.2017-1007.
Mohanta A, Mittal VK. Classifying speech of ASD affected and regular youngsters utilizing acoustic options. In: 2020 Nationwide convention on communications (NCC) Kharagpur, India. IEEE, 2020, pp. 1–6.
Mohanta A, Mittal VK. Evaluation and classification of speech sounds of youngsters with autism spectrum dysfunction utilizing acoustic options. Comput Speech Lang. 2022;72:101287.
Asgari M, Shafran I. Strong and correct options for detecting and diagnosing autism spectrum issues. Proceedings of the annual convention of the worldwide speech communication affiliation. Interspeech. 2013;2013:191–4.
Yankowitz LD, Schultz RT, Parish-Morris J. Pre- and paralinguistic vocal manufacturing in ASD: start via faculty age. Curr Psychiatry Rep. 2019;21:126.
Lee S, Yeo EJ, Kim S, Chung M. Information-driven speech options for detection of Korean-speaking youngsters with autism spectrum dysfunction*. Phonetics and Speech Sci. 2023;15:53–9.
Briend F, David C, Silleresi S, Malvy J, Ferré S, Latinus M. Voice acoustics permit classifying autism spectrum dysfunction with excessive accuracy. Transl Psychiatry. 2023;13:250.
MacFarlane H, Salem AC, Chen L, Asgari M, Fombonne E. Combining voice and language options improves automated autism detection. Autism Res. 2022;15:1288–300.
Lord C, Rutter M, Di Lavore P, Risi S, Gotham Ok, Bishop S. Autism and diagnostic remark schedule, Second Version (ADOS-2) Guide (Half I): Modules. 2012, pp. 1–4.
Sadiq S, Castellanos M, Moffitt J, Shyu M, Perry L, Messinger D. Deep studying based mostly multimedia information mining for autism spectrum dysfunction (ASD) prognosis. In: 2019 Worldwide convention on information mining workshops (ICDMW). IEEE. 2019, pp. 847–54.
Chen C-P, Gau SS-F, Lee C-C. Studying converse-level multimodal embedding to evaluate social deficit severity for autism spectrum dysfunction. In: 2020 IEEE worldwide convention on multimedia and expo (ICME). IEEE, 2020, pp. 1–6.
Eni M, Dinstein I, Ilan M, Menashe I, Meiri G, Zigel Y. Estimating autism severity in younger youngsters from speech indicators utilizing a deep neural community. IEEE Entry. 2020;8:139489–500.
Esler AN, Bal VH, Guthrie W, Wetherby A, Weismer SE, Lord C. The autism diagnostic remark schedule, toddler module: standardized severity scores. J Autism Dev Disord. 2015;45:2704–20.
Gotham Ok, Pickles A, Lord C. Standardizing ADOS scores for a measure of severity in autism spectrum issues. J Autism Dev Disord. 2009;39:693–705.
Dinstein I, Arazi A, Golan HM, Koller J, Elliott E, Gozes I, et al. The nationwide autism database of Israel: a useful resource for finding out autism threat elements, biomarkers, consequence measures, and therapy efficacy. J Mol Neurosci. 2020;70:1303–12.
Meiri G, Dinstein I, Michaelowski A, Flusser H, Ilan M, Faroy M, et al. The negev hospital-university-based (HUB) autism database. J Autism Dev Disord. 2017;47:2918–26.
American Psychiatric Affiliation. Diagnostic and statistical handbook of psychological issues. fifth ed. American Psychiatric Publishing: Arlington, VA; 2013. https://doi.org/10.1176/appi.books.9780890425596.744053.
Hus V, Gotham Ok, Lord C. Standardizing ADOS area scores: separating severity of social have an effect on and restricted and repetitive behaviors. J Autism Dev Disord. 2014;44:2400–12.
Hansen JHL, Najafian M, Lileikyte R, Irvin D, Rous B. Speech and language processing for assessing little one–grownup interplay based mostly on diarization and placement. Int J Speech Technol. 2019;22:697–709.
Kumar M, Kim SH, Lord C, Lyon TD, Narayanan S. Leveraging linguistic context in dyadic interactions to enhance automated speech recognition for kids. Comput Speech Lang. 2020;63:101101.
Padmini P, Gupta D, Zakariah M, Alotaibi YA, Bhowmick Ok. A easy speech manufacturing system based mostly on formant estimation of a tongue articulatory system utilizing human tongue orientation. IEEE Entry. 2021;9:4688–710.
Rusz J, Benova B, Ruzickova H, Novotny M, Tykalova T, Hlavnicka J, et al. Traits of motor speech phenotypes in a number of sclerosis. Mult Scler Relat Disord. 2018;19:62–9.
Boersma P, van Heuven V. Converse and unSpeak with Praat. Glot Int. 2001;5:341–7.
Pillai L, Sherly E. A deep studying based mostly analysis of articulation dysfunction and studying assistive system for autistic youngsters. Int J Nat Lang Comput. 2017;6:19–36.
Tamarit L, Goudbeek M, Scherer Ok. Spectral slope measurements in emotionally expressive speech. In: Proceedings of ISCA tutorial and analysis workshop (ITRW) on speech evaluation and processing for information discovery. ISCA, 2008, pp. 1–4.
Eyben F, Scherer KR, Schuller BW, Sundberg J, Andre E, Busso C, et al. The Geneva Minimalistic Acoustic Parameter Set (GeMAPS) for voice analysis and affective computing. IEEE Trans Have an effect on Comput. 2016;7:190–202.
Taqi AM, Awad A, Al-Azzo F, Milanova M. The affect of multi-optimizers and information augmentation on tensorflow convolutional neural community efficiency. In: Proceedings – IEEE 1st convention on multimedia data processing and retrieval, MIPR 2018. IEEE, 2018, 140–5.
Prechelt L. Early stopping — however when? In: Neural networks: tips of the commerce. Springer: Berlin, Heidelberg, 2012, pp. 53–67.
MacFarlane H, Salem AC, Bedrick S, Dolata JK, Wiedrick J, Lawley GO, et al. Consistency and reliability of automated language measures throughout expressive language samples in autism. Autism Res. 2023;16:802–16.
Tager-Flusberg H. Defining language phenotypes in autism. Clin Neurosci Res. 2006;6:219–24.
Tager-Flusberg H, Rogers S, Cooper J, Landa R, Lord C, Paul R, et al. Defining spoken language benchmarks and choosing measures of expressive language improvement for younger youngsters with autism spectrum issues. J Speech Lang Hear Res. 2009;52:643–52.
Vivanti G, Bottema-Beutel Ok, Turner-Brown L. Understanding and addressing restricted and repetitive behaviors in youngsters with autism. In: Scientific information to early interventions for kids with autism. Springer, 2020, pp. 61–77.
Avni I, Meiri G, Bar‐Sinai A, Reboh D, Manelis L, Flusser H, et al. Youngsters with autism observe social interactions in an idiosyncratic method. Autism Re. 2020;13:935–46.
Chong E, Clark-Whitney E, Southerland A, Stubbs E, Miller C, Ajodan EL, et al. Detection of eye contact with deep neural networks is as correct as human consultants. Nat Commun. 2020;11:6386.
Jones W, Klaiman C, Richardson S, Aoki C, Smith C, Minjarez M, et al. Eye-tracking-based measurement of social visible engagement in contrast with professional medical prognosis of autism. JAMA. 2023;330:854–65.
Perochon S, Di Martino JM, Carpenter KLH, Compton S, Davis N, Eichner B, et al. Early detection of autism utilizing digital behavioral phenotyping. Nat Med. 2023;29:2489–97.
Budman I, Meiri G, Ilan M, Faroy M, Langer A, Reboh D, et al. Quantifying the social signs of autism utilizing movement seize. Sci Rep. 2019;9:7712.
Frazier TW, Whitehouse AJO, Leekam SR, Carrington SJ, Alvares GA, Evans DW, et al. Reliability of the generally used and newly-developed autism measures. J Autism Dev Disord. 2023. https://doi.org/10.1007/s10803-023-05967-y.
Waizbard-Bartov E, Ferrer E, Younger GS, Heath B, Rogers S, Wu Nordahl C, et al. Trajectories of autism symptom severity change throughout early childhood. J Autism Dev Disord. 2021;51:227–42.
Maddox BB, Brodkin ES, Calkins ME, Shea Ok, Mullan Ok, Hostager J, et al. The accuracy of the ADOS-2 in figuring out autism amongst adults with complicated psychiatric circumstances. J Autism Dev Disord. 2017;47:2703.
Bishop SL, Lord C. Commentary: greatest practices and processes for evaluation of autism spectrum dysfunction – the supposed position of standardized diagnostic devices. J Youngster Psychol Psychiatry. 2023;64:834–8. https://doi.org/10.1111/JCPP.13802.
Klaiman C, White S, Richardson S, McQueen E, Walum H, Aoki C, et al. Knowledgeable clinician certainty in diagnosing autism spectrum dysfunction in 16-30-month-olds: a multi-site trial secondary evaluation. J Autism Dev Disord. 2022. https://doi.org/10.1007/S10803-022-05812-8.
Raz R, Weisskopf MG, Davidovitch M, Pinto O, Levine H. Variations in autism spectrum issues incidence by sub-populations in Israel 1992–2009: a complete inhabitants examine. J Autism Dev Disord. 2015;45:1062–9.
