Utilizing robots for voice and sound analysis in therapy: enhancing emotional understanding in children with autism spectrum disorders

Abstract

Exploring and understanding emotions when treating children with autism spectrum disorders (ASD) is of fundamental importance for both therapists and children themselves. People with ASD often use specific communication methods, which may make it difficult to express their feelings using conventional verbal and non-verbal techniques. Therefore, a deep analysis of the subtle aspects of their speech, intonation, rhythm, and other auditory forms of expression can provide valuable clues about their emotions, needs, and reactions to therapeutic activities. Children's emotional responses can manifest in many ways, including voice modulation, which can signal anger, sadness, or happiness. Therapists can better interpret the child's intentions and reactions to surrounding stimuli using voice analysis methods. For example, a flat tone of voice may indicate apathy or anxiety, while a high volume may indicate excitement or tension. Additionally, various unconventional sounds a child makes can provide valuable information about their emotional and mental state. To capture these signals, therapists can use advanced equipment for recording and analyzing sounds and robots equipped with image and sound recording functions, which help in therapy.

Keywords

• emotions
• sound analysis
• robot
• asd
• therapeutic interventions
• machine learning
• artificial intelligence