BC-AC Multimodal Emotional Speech Dataset (Partial Release)

To support research on multimodal speech emotion recognition (SER), we developed a dual-channel emotional speech database featuring synchronized recordings of bone-conducted (BC) and air-conducted (AC) speech. The recordings were conducted in a professionally treated anechoic chamber with 100 gender-balanced volunteers. AC speech was captured via a digital microphone on the left channel, while BC speech was recorded from an in-ear BC microphone on the right channel, both at a 44.1 kHz sampling rate to ensure high-fidelity audio. Each participant completed a 60-minute session consisting of two phases: emotion induction and expression. Participants first watched emotion-inducing video clips and reported their emotional state using a discrete label and a 0–5 intensity scale. They then read predefined prompts while maintaining the induced emotion, generating labeled utterances. The speech material included 480 sentences (120 per emotion: angry, happy, neutral, sad) selected from a standardized iFLYTEK corpus. Emotional and neutral utterances were alternated to minimize cognitive fatigue, and the material was evenly divided into four subsets to maintain emotional balance. Manual perceptual evaluation yielded recognition accuracies of 93.56% for emotional and 82.38% for neutral utterances, confirming data quality. After segmentation, the final dataset contains 24,191 labeled utterances.