Latin Music Features and CLAP Embeddings from 30-Second Audio Fragments

30-second audio fragments of Latin music are provided with extracted features. Each fragment includes a 512-dimensional CLAP embedding, 13 MFCCs, and a BPM value. The dataset is hosted on Kaggle, but details about the creator, size, and license are not specified.

Use Cases

• Train music genre classifiers based on MFCC and BPM features.
• Benchmark audio representation models using the provided 512D CLAP embeddings.
• Analyze rhythmic patterns in Latin music based on the BPM data.
• Develop similarity search systems for audio clips using the CLAP embeddings.

Strengths

• Includes a 512-dimensional CLAP embedding per audio sample, which is a modern audio representation.
• Provides 13 MFCCs, a standard feature set for audio analysis.
• Contains BPM (beats per minute) data for rhythmic analysis.

Limitations

• Row count and total dataset size are unknown, which may limit suitability assessment.
• Column-level documentation is absent; field semantics must be inferred after download.
• Description metadata is limited; actual data quality requires manual inspection after download.

Provenance

Source

Kaggle