Music Listening- Genre EEG dataset (MUSIN-G)

The dataset contains Electroencephalography (EEG) responses from 20 Indian participants, on 12 songs of different genres (from Indian Classical to Goth Rock). Each session indicates a song by its number. For the experiment, the participants were indicated to close their eyes indicated by a single beep, and the song was presented to them on speakers. After listening to each song, a double beep was presented, asking them to open their eyes and rate their familiarity and enjoyment to the song. The responses were taken on a scale of 1 to 5, where 1 meant most familiar or most enjoyable, and 5 meant least familiar or least enjoyable. The events timeline in segmented data must be ignored as these are inherited from rawdata本数据集包含20名印度参与者的脑电（Electroencephalography, EEG）反应数据，实验使用了12首不同流派的音乐（涵盖印度古典音乐至哥特摇滚）。每次实验环节以编号指代对应歌曲。 实验流程如下：首先通过单声蜂鸣提示参与者闭眼，随后通过扬声器播放对应歌曲。每首歌曲播放完毕后，会发出双声蜂鸣，提示参与者睁眼并对该歌曲的熟悉程度与喜爱程度进行评分。评分采用1至5分的量表：1代表最熟悉或最喜爱，5代表最不熟悉或最不喜爱。 需注意，分段数据中的事件时间线可忽略，因其直接继承自原始数据。

搜集汇总

背景与挑战

背景概述

该数据集记录了20名参与者在听12首不同风格音乐时的EEG反应，包括他们对音乐的熟悉度和享受度评分。数据集大小为10.12GB，包含1685个文件，适用于音乐与脑电反应相关的研究。