Computational Analysis of Yaredawi YeZema Silt in Ethiopian Orthodox Tewahedo Church Chants
Mequanent Argaw Muluneh, Yan-Tsung Peng, Li Su

TL;DR
This paper introduces a new dataset and neural network-based classification method for analyzing Yaredawi YeZema Silt, a mode of Ethiopian Orthodox chant, using music information retrieval techniques to enhance understanding and preservation.
Contribution
It presents the first dataset and classification experiments specifically targeting Yaredawi YeZema Silt in EOTC chants, advancing computational musicology in this cultural domain.
Findings
Effective pitch contour features for classification
Neural network classifier achieves promising results
Dataset availability promotes future research
Abstract
Despite its musicological, cultural, and religious significance, the Ethiopian Orthodox Tewahedo Church (EOTC) chant is relatively underrepresented in music research. Historical records, including manuscripts, research papers, and oral traditions, confirm Saint Yared's establishment of three canonical EOTC chanting modes during the 6th century. This paper attempts to investigate the EOTC chants using music information retrieval (MIR) techniques. Among the research questions regarding the analysis and understanding of EOTC chants, Yaredawi YeZema Silt, namely the mode of chanting adhering to Saint Yared's standards, is of primary importance. Therefore, we consider the task of Yaredawi YeZema Silt classification in EOTC chants by introducing a new dataset and showcasing a series of classification experiments for this task. Results show that using the distribution of stabilized pitch…
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Taxonomy
TopicsAfrican history and culture analysis · Archaeology and Historical Studies · Water management and technologies
MethodsDense Connections · Feedforward Network · Mixup · CutMix · SAINT
