Update README.md

README.md

@@ -7,6 +7,7 @@ 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**
@@ -22,4 +23,20 @@ Popular Hooks, a shared multimodal music dataset consisting of **38,694** popula
 - Structure
 - Genre
 - Emotion(Russell's 4Q)
-- Region
+- 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.