NEXTLab-ZJU/popular-hook

--- tags: - music - midi - emotion size_categories: - 10K<n<100K --- # Popular Hooks This is the dataset repository for the paper: Popular Hooks: A Multimodal Dataset of Musical Hooks for Music Understanding and Generation, in 2024 IEEE International Conference on Multimedia and Expo Workshops (ICMEW). ## 1. Introduction Popular Hooks, a shared multimodal music dataset consisting of **38,694** popular musical hooks for music understanding and generation; this dataset has the following key features: - **Multimodal Music Data** - **Accurate Time Alignment** - **Rich Music Annotations** ## 2. Modalities - Midi - Lyrics - Video (Youtube link provided, you need to download it by yourself) - Audio ## 3. High Level Music Information - Melody - Harmony - Structure - Genre - Emotion(Russell's 4Q) - Region ## 4. Dataset File Structure - info_tables.xlsx: it contains a list describing the baisc information of each midi file (index, path, song name, singer, song url, genres, youtube url, youtube video start time and end time/duration, language, tonalities) - midi/{index}/{singer_name}/{song_name}: - complete_text_emotion_result.csv: it contains the emotion class(4Q) which is predicted with the total lyrics of the song. - song_info.json: it contains the song's section info, theorytab DB url and genres info. - total_lyrics.txt: it contains the song's complete lyrics which is collected from music API(lyricsGenius, NetEase, QQMusic) - youtube_info.json: it contains the url of the song in Youtube, the start time and end time/duration of the video section. - ./{section} - {section}.mid: the section in midi format - {section}.txt: it contains the tonalites of the section. - {section}_audio_emotion_result.csv: it contains the emotion class(4Q) which is predicted with the audio of the section. - {section}_lyrics.csv: it contains the lyrics of the section. - {section}_midi_emotion_result.csv: it contains the emotion class(4Q) which is predicted with the midi of the section. - {section}_multimodal_emotion_result.csv: it contains the emotion class(4Q) which is selected from the multimodal emotions of the section. - {section}_text_emotion_result.csv: it contains the emotion class(4Q) which is predicted with the lyrics of the section. - {section}_video_emotion_result.csv: it contains the emotion class(4Q) which is predicted with the video of the section. ## 5. Demo <img src='https://huggingface.co/datasets/NEXTLab-ZJU/popular-hook/resolve/main/imgs/popular_hooks_demo.png'>--- 标签： - 音乐 - MIDI（Midi） - 情感 样本量级： - 10000 < 样本量 < 100000 --- # 流行副歌数据集（Popular Hooks） 本数据集仓库对应发表于2024年IEEE国际多媒体与博览会研讨会（ICMEW）的论文《流行副歌：用于音乐理解与生成的多模态音乐副歌数据集》。 ## 1. 数据集简介 流行副歌数据集（Popular Hooks）是一款共享的多模态音乐数据集，包含38694条热门音乐副歌，用于音乐理解与生成任务；该数据集具备以下核心特性： - **多模态音乐数据** - **精准时序对齐** - **丰富的音乐标注信息** ## 2. 数据模态 - MIDI（Midi） - 歌词 - 视频（提供YouTube链接，需自行下载） - 音频 ## 3. 高阶音乐信息 - 旋律 - 和声 - 乐曲结构 - 音乐流派 - 情感标注（罗素四象限模型，Russell's 4Q） - 地域归属 ## 4. 数据集文件结构 - info_tables.xlsx：包含各MIDI文件的基础信息列表，涵盖索引、文件路径、歌曲名称、演唱者、歌曲链接、音乐流派、YouTube链接、YouTube视频的起止时间/时长、语言、调式信息 - MIDI/{index}/{singer_name}/{song_name}： - complete_text_emotion_result.csv：包含基于整首歌曲完整歌词预测得到的情感类别（四象限模型） - song_info.json：包含歌曲段落信息、theorytab数据库链接及音乐流派信息 - total_lyrics.txt：包含从音乐API（lyricsGenius、网易云音乐、QQ音乐）采集的整首歌曲完整歌词 - youtube_info.json：包含该歌曲的YouTube链接、对应视频片段的起止时间/时长 - ./{section} 目录： - {section}.mid：该段落的MIDI格式文件 - {section}.txt：包含该段落的调式信息 - {section}_audio_emotion_result.csv：包含基于该段落音频预测得到的情感类别（四象限模型） - {section}_lyrics.csv：包含该段落的歌词内容 - {section}_midi_emotion_result.csv：包含基于该段落MIDI文件预测得到的情感类别（四象限模型） - {section}_multimodal_emotion_result.csv：包含从该段落多模态情感信息中筛选得到的最终情感类别（四象限模型） - {section}_text_emotion_result.csv：包含基于该段落歌词预测得到的情感类别（四象限模型） - {section}_video_emotion_result.csv：包含基于该段落视频预测得到的情感类别（四象限模型） ## 5. 示例演示 <img src='https://huggingface.co/datasets/NEXTLab-ZJU/popular-hook/resolve/main/imgs/popular_hooks_demo.png'>