Audio features are paired with emotion and genre labels for analysis. The dataset is multimodal, combining audio signal data with categorical annotations. Specific row counts, column details, and creation metadata are unavailable.
Use Cases
- Classify music genre labels using extracted audio features.
- Analyze correlations between audio features and emotion labels.
- Train a multimodal model to predict emotion from audio characteristics.
Strengths
- Data is multimodal, integrating audio features with categorical labels.
- Focuses on two analytically rich annotation types: genre and emotion.
Limitations
- Unknown sample size prevents assessment of statistical power.
- Data collection methodology and potential label biases are unspecified.
- Absence of column details limits understanding of feature granularity.
Provenance
- Source
- Kaggle
- Collection Method
- null
- Time Range
- null
- Freshness
- null
- Geography
- null