CNEV: A corpus of Chinese nonverbal emotional vocalizations with a database of emotion category, valence, arousal, and gender.

Abstract

Nonverbal emotional vocalizations play a crucial role in conveying emotions during human interactions. Validated corpora of these vocalizations have facilitated emotion-related research and found wide-ranging applications. However, existing corpora have lacked representation from diverse cultural backgrounds, which may limit the generalizability of the resulting theories. The present paper introduces the Chinese Nonverbal Emotional Vocalization (CNEV) corpus, the first nonverbal emotional vocalization corpus recorded and validated entirely by Mandarin speakers from China. The CNEV corpus contains 2415 vocalizations across five emotion categories: happiness, sadness, fear, anger, and neutrality. It also includes a database containing subjective evaluation data on emotion category, valence, arousal, and speaker gender, as well as the acoustic features of the vocalizations. Key conclusions drawn from statistical analyses of perceptual evaluations and acoustic analysis include the following: (1) the CNEV corpus exhibits adequate reliability and high validity; (2) perceptual evaluations reveal a tendency for individuals to associate anger with male voices and fear with female voices; (3) acoustic analysis indicates that males are more effective at expressing anger, while females excel in expressing fear; and (4) the observed perceptual patterns align with the acoustic analysis results, suggesting that the perceptual differences may stem not only from the subjective factors of perceivers but also from objective expressive differences in the vocalizations themselves. For academic research purposes, the CNEV corpus and database are freely available for download at https://osf.io/6gy4v/ .