Improve dataset card: add metadata and links

README.md

@@ -1,20 +1,35 @@
+---
+task_categories:
+- other
+license: cc-by-4.0
+arxiv: 2506.01482
+language:
+- en
+tags:
+- audio
+- music
+- stage-lighting
+- audio-visual
+pretty_name: RPMC-L2
+---
+
 # RPMC-L2
 
-The description is generated by Grok3.
+[**Paper**](https://huggingface.co/papers/2506.01482) | [**Code**](https://github.com/RS2002/Skip-BART) | [**Model**](https://huggingface.co/RS2002/Skip-BART) | [**Zenodo**](https://zenodo.org/records/14854217)
 
-Other download link: [RPMC-L2](https://zenodo.org/records/14854217)
+The Rock, Punk, Metal, and Core - Livehouse Lighting (RPMC-L2) dataset contains synchronized music and lighting data collected from professional live performance venues. This is the first stage lighting dataset designed to treat Automatic Stage Lighting Control (ASLC) as a generative task, introduced in the paper "Automatic Stage Lighting Control: Is it a Rule-Driven Process or Generative Task?".
 
 ## Dataset Description
 
-- **Repository:** [RS2002/Skip-BART: Official Repository for The Paper, Automatic Stage Lighting Control: Is it a Rule-Driven Process or Generative Task?](https://github.com/RS2002/Skip-BART)
-- **Paper:** [Automatic Stage Lighting Control: Is it a Rule-Driven Process or Generative Task?](https://arxiv.org/abs/2506.01482)
+- **Repository:** [RS2002/Skip-BART](https://github.com/RS2002/Skip-BART)
+- **Paper:** [Automatic Stage Lighting Control: Is it a Rule-Driven Process or Generative Task?](https://huggingface.co/papers/2506.01482)
 - **Contact:** zzhaock@connect.ust.hk
 - **Collector:** Zijian Zhao
-- **Dataset Processer:** Dian Jin
+- **Dataset Processor:** Dian Jin
 - **Organization:** [Tokamak Disruption Band](https://tokamak-disruption.netlify.app/)
 - **Dataset Summary:**
   The Rock, Punk, Metal, and Core - Livehouse Lighting (RPMC-L2) dataset contains synchronized music and lighting data collected from professional live performance venues in the genres of Rock, Punk, Metal, and Core. The dataset includes 699 files in HDF5 format, totaling approximately 40 GB, designed to study the relationship between music features and lighting effects in live performances.
-- **Tasks:** Music-to-Lighting Relationship Analysis, Audio-Visual Synchronization, Cross-Domain Tasks.
+- **Tasks:** Music-to-Lighting Relationship Analysis, Audio-Visual Synchronization, Cross-Domain Generative Tasks.
 
 ## Dataset Structure
 
@@ -57,23 +72,11 @@ The dataset was created to facilitate research on the relationship between music
 
 ### Source Data
 
-- Initial Data Collection:
-
+- **Initial Data Collection:**
   Data was collected from professional live performance venues hosting Rock, Punk, Metal, and Core music genres. Music features were extracted from audio recordings, and lighting data was captured as threshold values (Hue, Saturation, Value) synchronized with the audio.  
-
-  - **Total Size:** ~40 GB  
-  - **Collection Method:** Professional live performance venues  
-  - **File Format:** HDF5 (`.h5`)
-
-- **Who are the source data producers?**
-  The data was collected by researchers or professionals in live music venues, capturing synchronized audio and lighting data.
-
-### Annotations
-
-- **Annotation Process:**
-  The dataset includes music features (e.g., mel spectrogram, MFCC) and lighting data (threshold values for Hue, Saturation, Value) automatically extracted and synchronized during data collection. No manual annotations were provided.  
-- **Who are the annotators?**
-  The dataset creators processed and organized the data using automated feature extraction tools.
+- **Total Size:** ~40 GB  
+- **Collection Method:** Professional live performance venues  
+- **File Format:** HDF5 (`.h5`)
 
 ## Citation
 
@@ -84,5 +87,4 @@ The dataset was created to facilitate research on the relationship between music
   journal={arXiv preprint arXiv:2506.01482},
   year={2025}
 }
-```
-
+```