Back to results

Massachusetts Institute of Technology

Comparative Analysis of an Armenian Hymn Through Digital Signal Processing and Music Information Retrieval

Abstract

dc:description.abstract

Armenian music has existed for centuries, dating back to several millennia BC. The music has undoubtedly evolved over time, whether passed down traditionally or through reimaginations of the original piece. Despite straying from the original versions, the music nonetheless keeps the spirit and tradition behind them intact. This thesis will compare and analyze the harmonic differences in a famous Armenian Hymn, Տէր Ողորմեա (“Der Voghormia”, meaning “Lord Have Mercy”). The baseline version will be the one that is found in the 20th-century manuscript written by Gomidas Vartabed, and will be compared against later renditions. This will be performed by using several different techniques and algorithms from the Digital Signal Processing (DSP) and Music Information Retrieval (MIR) fields. The final products will be implemented through Python programming, along with related helper packages and toolkits.

Degree

thesis:*
Name thesis:degree_name
Master
Department dc:contributor.department
Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science
Grantor dc:publisher
Massachusetts Institute of Technology
Year dc:date.issued
2022

Author and committee

dc:creator, dc:contributor.*
Author dc:creator
  • Bouhanna, Jack
Advisors dc:contributor.advisor
  • Saraydarian, Garo
  • Hagelstein, Peter

Rights

dc:rights
Statement dc:rights
  • In Copyright - Educational Use Permitted
  • Copyright MIT

Identifiers

dc:identifier.*
Handle dc:identifier.uri
https://hdl.handle.net/1721.1/144683
OAI identifier oai:identifier
oai:dspace.mit.edu:1721.1/144683

Chain of custody

source
Harvested from
MIT
Base URL
dspace.mit.edu/oai/request
Last updated
2026-07-22
Source record
OAI-PMH GetRecord
related terms
citation

Bouhanna, Jack. Comparative Analysis of an Armenian Hymn Through Digital Signal Processing and Music Information Retrieval. Massachusetts Institute of Technology, 2022. https://hdl.handle.net/1721.1/144683