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Voice Parameter Analysis for Early Detection of Autism in Children

International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Year of Publication: 2021
Anasuodei Moko, Ledisi G. Kabari

Anasuodei Moko and Ledisi G Kabari. Voice Parameter Analysis for Early Detection of Autism in Children. International Journal of Computer Applications 183(12):25-29, June 2021. BibTeX

	author = {Anasuodei Moko and Ledisi G. Kabari},
	title = {Voice Parameter Analysis for Early Detection of Autism in Children},
	journal = {International Journal of Computer Applications},
	issue_date = {June 2021},
	volume = {183},
	number = {12},
	month = {Jun},
	year = {2021},
	issn = {0975-8887},
	pages = {25-29},
	numpages = {5},
	url = {},
	doi = {10.5120/ijca2021921432},
	publisher = {Foundation of Computer Science (FCS), NY, USA},
	address = {New York, USA}


Autism Spectrum Disorder (ASD) is categorized by social, behavioral and must crucially communication deficiencies. Early detection is necessary for an improved positive result in therapy. This paper proposes a voice parameter analysis for the early detection of ASD in children. The Study used MATLAB programming software to display the signal analysis of an obtained voice data from an autistic and a normal child. The key experimental result shows a major difference in both voices in the time-domain, frequency, and spectrogram signal view. It is seen that the power spectrum (dB) set off with a high pitch level, at -50db for the autistic child, while the normal child is slightly below but closer to -60db and it remained relatively stable for an autistic child along the normalized frequency within 0.58hz -1.0hz. The paper thus recommends early voice screening of Autism Spectrum Disorder (ASD) as a significant first step to identify children at risk of the disease development and will need additional evaluation, intervention, and services.


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Signal, voice, autism spectrum disorder, analysis, parameters