@article{(Open Science Index):https://publications.waset.org/pdf/10012604,
	  title     = {Voice Features as the Diagnostic Marker of Autism},
	  author    = {Elena Lyakso and  Olga Frolova and  Yuri Matveev},
	  country	= {},
	  institution	= {},
	  abstract     = {The aim of the study is to determine the acoustic features of voice and speech of children with autism spectrum disorders (ASD) as a possible additional diagnostic criterion. The participants in the study were 95 children with ASD aged 5-16 years, 150 typically development (TD) children, and 103 adults – listening to children’s speech samples. Three types of experimental methods for speech analysis were performed: spectrographic, perceptual by listeners, and automatic recognition. In the speech of children with ASD, the pitch values, pitch range, values of frequency and intensity of the third formant (emotional) leading to the “atypical” spectrogram of vowels are higher than corresponding parameters in the speech of TD children. High values of vowel articulation index (VAI) are specific for ASD children’s speech signals. These acoustic features can be considered as diagnostic marker of autism. The ability of humans and automatic recognition of the psychoneurological state of children via their speech is determined.},
	    journal   = {International Journal of Psychological and Behavioral Sciences},
	  volume    = {16},
	  number    = {7},
	  year      = {2022},
	  pages     = {377 - 382},
	  ee        = {https://publications.waset.org/pdf/10012604},
	  url   	= {https://publications.waset.org/vol/187},
	  bibsource = {https://publications.waset.org/},
	  issn  	= {eISSN: 1307-6892},
	  publisher = {World Academy of Science, Engineering and Technology},
	  index 	= {Open Science Index 187, 2022},
	}