HKU Data Repository
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HKU956: Dataset in "Detecting Music-Induced Emotion Based on Acoustic Analysis and Physiological Sensing: A Multimodal Approach"

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Version 4 2022-11-09, 01:37
Version 3 2022-10-31, 03:09
Version 2 2022-09-19, 06:20
Version 1 2022-09-14, 07:18
posted on 2022-11-09, 01:37 authored by Xiao HuXiao Hu, Fanjie Li, Ruilun LiuRuilun Liu


HKU956 is a multimodal dataset for analyzing listeners’ emotions and physiological responses induced by music. Five kinds of peripheral physiological signals (i.e., heart rate, electrodermal activity, blood volume pulse, inter-beat interval, and skin temperature) of 30 participants (18 females) were recorded as they listened to music within a period of 40 minutes. Each participant listened to 10 or more songs, and their physiological signals were aligned with the 956 listening records. Participants reported their emotions induced by each song in the arousal and valence dimensions in a scale of [-10, 10].   In addition, participants' personality traits were measured by the Ten Item Personality Measure (TIPI). The raw score in each of the five personality dimensions were presented, together with “high” or “low” categories derived from the TIPI norms provided by Gosling ( Last but not least, the original audio files of a total of 592 unique music pieces were presented in this dataset. These audio files were originally obtained from with CC-BY Licenses. 


├─14.09.2022(GMT+8) - First online date

├─31.10.2022(GMT+8) - Posted date

└─07.11.2022(GMT+8) - (1) Add the "play_duration" (i.e., Length of time a user plays a song) column into the file "3. AV_ratings.csv"; (2) Fill the missing value of the "valence_rating" column for the record with participant_id=hku1929, song_no=7, song_id=1119024 in the file "3. AV_ratings.csv"

Please cite the following paper when using this dataset

Hu, X.; Li, F.; Liu, R. Detecting Music-Induced Emotion Based on Acoustic Analysis and Physiological Sensing: A Multimodal Approach. Applied Science. 2022, 12, 9354. (free text available through Open Access) 


National Natural Science Foundation of China (No. 61703357)

Research Grants Council of the Hong Kong S. A. R., China (No. HKU 17607018)


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