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Emotional Prosody in Adverse Acoustic Conditions : Investigating effects of emotional prosody and noise-vocoding on speech perception and emotion recognition

Speech perception is a fundamental function of successful vocal communication, and through prosody, we can communicate different emotions. The ability to recognize emotions is important in social interaction. Emotional prosody facilitates emotion recognition in vocal communication. Acoustic conditions are not always optimal, due to either environmental disturbances or hearing loss. When perceiving speech and recognizing emotions we make use of multimodal sources of information. The effect of noise-vocoding on speech perception and emotion recognition can increase the knowledge of these abilities. The effect of emotional prosody on speech perception and emotion recognition ability in adverse acoustic conditions is not widely explored. To explore the role of emotional prosody during adverse acoustic conditions, an online test was created. 18 participants (8 women) listened to semantically neutral sentences with different emotions expressed in prosody and presented with five different levels of noise (NV1, NV3, NV6, NV12, and Clear) using noise-vocoding. Participants’ task was to reproduce the spoken words and identify the expressed emotion (happy, surprised, angry, sad, or neutral). A Reading span test was included to investigate any potential correlation between working memory capacity and the ability to recognize emotions in prosody. Statistical analysis suggests speech perception could be facilitated by emotional prosody when sentences are noise-vocoded. The ability to recognize emotions in emotional prosody differentiated between the emotions on the different noise levels. The ability to recognize anger was least affected by noise-vocoding, and sadness was most affected. Correlation analysis shows no significant result between working memory capacity and emotion recognition accuracy.

Identiferoai:union.ndltd.org:UPSALLA1/oai:DiVA.org:liu-187811
Date January 2022
CreatorsIvarsson, Cecilia
PublisherLinköpings universitet, Institutionen för datavetenskap, Linköpings universitet (Linköping)
Source SetsDiVA Archive at Upsalla University
LanguageEnglish
Detected LanguageEnglish
TypeStudent thesis, info:eu-repo/semantics/bachelorThesis, text
Formatapplication/pdf
Rightsinfo:eu-repo/semantics/openAccess

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