Abstract
In this work, we investigated the work of a neural network for recognizing speech in the Mongolian language and the emotional state in it. For the experiment, we used four commonly used words, which are composed of frequently used consonants and vowels. Emotional states in the speech were selected taking into account further research on changes in human mental disorders. For the analysis, we used a database of speeches of 12 men and women with eight types of emotions. Neural eat recognizes words by syllables with an efficiency of up to 96 percent, and emotions - up to 80 percent. These results show that for further analysis of human mental disorders, it remains only to collect a database from the speeches of patients of the relevant medical institutions.
Sign-in/Register to access full text options 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
