Zema Dataset: A Comprehensive Study of Yaredawi Zema with a Focus on Horologium Chants
Mequanent Argaw Muluneh, Yan-Tsung Peng, Worku Abebe Degife, Nigussie Abate Tadesse, Aknachew Mebreku Demeku, Li Su
TL;DR
The paper addresses the scarcity of computational resources for Ethiopian Orthodox Tewahedo Church chants by introducing a feature-rich Se'atat Zema dataset (Horologium chant) that pairs audio with lyric text and reading-tone labels. It details data collection from a single Horologium source, rigorous audio/text preprocessing, and a multi-step annotation pipeline capturing word-level timings, chanting options, and mode labels, along with quality validation. A preliminary case study using a support vector machine with MFCC features demonstrates the dataset's viability for chanting-mode classification, achieving 69.11% accuracy and highlighting Ezil as the most distinguishable mode. Overall, the dataset (approximately 10.21 hours and 369 clips) enables lyric transcription, lyric-to-audio alignment, and generation tasks, offering a valuable resource for MIR research and the cultural preservation of Yaredawi Zema.
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.
