A collection of audio files tagged with emotional labels across multiple music genres. The dataset is hosted on Kaggle, but its size, specific creation date, and original author are not detailed in the provided metadata. Columns and exact data formats are unknown.
Use Cases
- Train a model to classify music by perceived emotion (inferred from domain, verify after download)
- Develop a music recommendation system based on emotional tags (inferred from domain, verify after download)
- Analyze acoustic features correlated with different emotional states in music (inferred from domain, verify after download)
Strengths
- Published on Kaggle, a platform with an active data science community.
- The title and description suggest coverage of multiple music genres.
Limitations
- Metadata is minimal; actual content requires verification after download.
- Row count and file size are unknown, which may limit suitability assessment.
- Column-level documentation is absent; field semantics must be inferred after download.