What question did this study set out to answer?

The research aims to create and validate a dataset of emotional speech that incorporates personal pronouns in Mandarin Chinese.

March 7, 2026Open Access

A validated Mandarin Chinese Auditory Emotion Database of Subject-Personal-Pronoun Sentences (MCAE-SPPS)

Key Points

The research aims to create and validate a dataset of emotional speech that incorporates personal pronouns in Mandarin Chinese.
Developed a dataset of 200 sentences spoken by six actors in various emotions.
Collected emotional labels and intensity ratings from 720 native Mandarin speakers.
Recorded a total of 6,675 emotional utterances categorized by emotion and pronoun type.
The dataset includes recordings labeled with six emotions and varying degrees of intensity.
Inter-rater reliability was deemed acceptable, indicating consistency in emotion labeling.
Strong relationships were found between acoustic features of the speech and emotion recognition accuracy.

Abstract

Emotional expression in speech varies with grammatical subjects, including personal pronouns. This study reports the development and validation of a novel Mandarin Chinese auditory emotional speech dataset comprising sentences with first-, second-, and third-person pronouns. Six professionally trained actors recorded 200 semantically meaningful sentences in a neutral tone and six basic emotions: happiness, sadness, anger, fear, disgust, and surprise. Emotional labels and intensity ratings were provided by 720 native Chinese-speaking college students. The final dataset includes 6,675 validated recordings, including Neutral (1,169), Sadness (1,187), Anger (671), Surprise (969), Disgust (738), Happiness (785), and Fear (671) utterances. Of these, 2,729 recordings contain first-person pronouns, 2,608 contain second-person pronouns, and 1,338 contain third-person pronouns. The dataset demonstrated acceptable inter-rater reliability and robust associations between acoustic features and emotion recognition performance. Each recording includes the raw waveform file, emotion recognition rates, perceived intensity ratings, and a comprehensive set of extracted acoustic features. This validated emotional speech corpus offers a unique and valuable resource for research in linguistics, psychological science, neuroscience, and clinical rehabilitation.

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