Music Berkeley Emotions: Audio Data for Affective Computing

A dataset for music emotion recognition and affective computing, sourced from the Hugging Face platform. It was created by author akhmedsakip and last updated in May 2023.

Use Cases

• Train models for Music Emotion Recognition using audio features for Affective Computing tasks.
• Perform Music Information Retrieval analysis on audio data tagged with emotion labels.
• Analyze the relationship between audio characteristics and perceived emotions within the dataset's scope.

Strengths

• Last updated in May 2023, indicating recent maintenance.
• Tagged for specific domains: Affective Computing, Music Emotion, and Music Information Retrieval.
• Includes a geographic tag indicating data from the United States.

Limitations

• Critical metadata is unknown, including row count, column names, sample data, and file formats.
• The raw description states 'More Information needed', suggesting incomplete documentation.
• License and organizational provenance are unspecified, which may restrict usage.

Provenance

Source

Hugging Face (user akhmedsakip)

Freshness

2023-05-01

Geography

United States