Arabic Music Genre Audio Dataset – Part 1 (Egyptian, Khaliji, and Pop)
Year: 2026
Type: dataset
Abstract: This dataset is Part 1 of a two-part Arabic music audio corpus developed for research in music information retrieval and Arabic music classification. It contains 600 WAV audio excerpts organized into three categories: Egyptian, Khaliji, and Pop, with 200 recordings per category. Each audio file has a corresponding symbolic state-sequence TXT file available in Arabic Music Genre Symbolic Sequence Dataset – Part 1 (Egyptian, Khaliji, and Pop) (https://doi.org/10.7910/DVN/POV3TU). The corpus was constructed using a structured collection and balancing methodology. Songs were manually collected and organized by Arabic music category, and within-category clustering was used during corpus development to identify internal musical variations associated with characteristics such as rhythmic patterns, instrumentation, regional style, and vocal accent. The corpus was incrementally expanded while considering the representation of these internal groups. The middle region of each recording was retained for the released audio representation after preliminary experiments showed it to provide stronger classification performance than the intro and outro regions.
Source: Harvard Dataverse
DOI: 10.7910/dvn/bjlje8
Authors: Soboh, Lama, Islam Elkabani
Institutions: Beirut Arab University, University of Cincinnati
Language: English
Topic: Music and Audio Processing
Subfield: Signal Processing
Field: Computer Science
Domain: Physical Sciences
Open Access status: green
OpenAlex ID: W7204453896