Acoustic Features Distinguishing Emotions in Swedish Speech

Abstract

Few studies have examined which acoustic features of speech can be used to distinguish between different emotions, and how combinations of acoustic parameters contribute to identification of emotions. The aim of the present study was to investigate which acoustic parameters in Swedish speech are most important for differentiation between, and identification of, the emotions anger, fear, happiness, sadness, and surprise in Swedish sentences. One-way ANOVAs were used to compare acoustic parameters between the emotions and both simple and multiple logistic regression models were used to examine the contribution of different acoustic parameters to differentiation between emotions. Results showed differences between emotions for several acoustic parameters in Swedish speech: surprise was the most distinct emotion, with significant differences compared to the other emotions across a range of acoustic parameters, while anger and happiness did not differ from each other on any parameter. The logistic regression models showed that fear was the best-predicted emotion while happiness was most difficult to predict. Frequency- and spectral-balance-related parameters were best at predicting fear. Amplitude- and temporal-related parameters were most important for surprise, while a combination of frequency-, amplitude- and spectral balance-related parameters are important for sadness. Assuming that there are similarities between acoustic models and how listeners infer emotions in speech, results suggest that individuals with hearing loss, who lack abilities of frequency detection, may compared to normal hearing individuals have difficulties in identifying fear in Swedish speech. Since happiness and fear relied primarily on amplitude- and spectral-balance-related parameters, detection of them are probably facilitated more by hearing aid use.

Keywords: Acoustic features; Emotions; Speech.