Zema Dataset: A Comprehensive Study of Yaredawi Zema with a Focus on Horologium Chants

TL;DR

This paper introduces a comprehensive 10-hour dataset of Yaredawi Zema chants, including detailed annotations, to facilitate computational analysis and preservation of Ethiopian Orthodox liturgical music.

Contribution

It provides the first detailed, annotated dataset of EOTC chants with boundary, tone, and mode labels, supporting future research in music analysis and preservation.

Findings

Dataset includes 369 instances with detailed annotations.

Rigorous quality assurance ensures data reliability.

Aims to promote research in lyrics transcription and music generation.

Abstract

Computational music research plays a critical role in advancing music production, distribution, and understanding across various musical styles worldwide. Despite the immense cultural and religious significance, the Ethiopian Orthodox Tewahedo Church (EOTC) chants are relatively underrepresented in computational music research. This paper contributes to this field by introducing a new dataset specifically tailored for analyzing EOTC chants, also known as Yaredawi Zema. This work provides a comprehensive overview of a 10-hour dataset, 369 instances, creation, and curation process, including rigorous quality assurance measures. Our dataset has a detailed word-level temporal boundary and reading tone annotation along with the corresponding chanting mode label of audios. Moreover, we have also identified the chanting options associated with multiple chanting notations in the manuscript by annotating them accordingly. Our goal in making this dataset available to the public 1 is to encourage more research and study of EOTC chants, including lyrics transcription, lyric-to-audio alignment, and music generation tasks. Such research work will advance knowledge and efforts to preserve this distinctive liturgical music, a priceless cultural artifact for the Ethiopian people.