Comparing Emotion Recognition and Word Recognition in Background Noise.

Purpose Word recognition in quiet and in background noise has been thoroughly investigated in previous research to establish segmental speech recognition performance as a function of stimulus characteristics (e.g., audibility). Similar methods to investigate recognition performance for suprasegmental information (e.g., acoustic cues used to make judgments of talker age, sex, or emotional state) have not been performed. In this work, we directly compared emotion and word recognition performance in different levels of background noise to identify psychoacoustic properties of emotion recognition (globally and for specific emotion categories) relative to word recognition. Method Twenty young adult listeners with normal hearing listened to sentences and either reported a target word in each sentence or selected the emotion of the talker from a list of options (angry, calm, happy, and sad) at four signal-to-noise ratios in a background of white noise. Psychometric functions were fit to the recognition data and used to estimate thresholds (midway points on the function) and slopes for word and emotion recognition. Results Thresholds for emotion recognition were approximately 10 dB better than word recognition thresholds, and slopes for emotion recognition were half of those measured for word recognition. Low-arousal emotions had poorer thresholds and shallower slopes than high-arousal emotions, suggesting greater confusion when distinguishing low-arousal emotional speech content. Conclusions Communication of a talker's emotional state continues to be perceptible to listeners in competitive listening environments, even after words are rendered inaudible. The arousal of emotional speech affects listeners' ability to discriminate between emotion categories.