This thesis introduces a music visualization system for stereophonic source separated music. Music visualization systems are a popular way to represent information from audio signals through computer graphics. Visualization can help people better understand music and its complex and interacting elements. This music visualization system extracts pitch, panning, and loudness features from source separated audio files to create the visual. Most state-of-the art visualization systems develop their visual representation of the music from either the fully mixed final song recording, where all of the instruments and vocals are combined into one file, or from the digital audio workstation (DAW) data containing multiple independent recordings of individual audio sources. Original source recordings are not always readily available to the public so music source separation (MSS) can be used to obtain estimated versions of the audio source files. This thesis surveys different approaches to MSS and music visualization as well as introduces a new music visualization system specifically for source separated music.
","abstract_html":"<p>This thesis introduces a music visualization system for stereophonic source separated music. Music visualization systems are a popular way to represent information from audio signals through computer graphics. Visualization can help people better understand music and its complex and interacting elements. This music visualization system extracts pitch, panning, and loudness features from source separated audio files to create the visual. Most state-of-the art visualization systems develop their visual representation of the music from either the fully mixed final song recording, where all of the instruments and vocals are combined into one file, or from the digital audio workstation (DAW) data containing multiple independent recordings of individual audio sources. Original source recordings are not always readily available to the public so music source separation (MSS) can be used to obtain estimated versions of the audio source files. This thesis surveys different approaches to MSS and music visualization as well as introduces a new music visualization system specifically for source separated music.</p>","abstract_has_math":false,"creators":["Chookaszian, Hannah Eileen"],"institution":null,"degree_name":"MS in Electrical Engineering","degree_level":null,"degree_discipline":"Electrical Engineering","degree_department":null,"school":null,"contributors":["Wayne Pilkington","Electrical Engineering","College of Engineering"],"advisors":[],"committee_chairs":[],"committee_members":[],"year":2022,"date_issued":"2022-06-01T07:00:00Z","date_published":"2022-06-01T07:00:00Z","updated_at":"2026-07-24T01:32:13Z","subjects":["Digital Signals Processing","Music Information Retrieval","Music Source Separation","Music Information Visualization","Signal Processing"],"languages":[],"rights":[],"rights_urls":[],"identifier_entries":[{"key":"dc:identifier","label":"Identifier","values":["10.15368/theses.2022.44"],"render_values":[{"text":"10.15368/theses.2022.44","href":"https://doi.org/10.15368/theses.2022.44","code":true}]}]},"links":{"outbound_url":"https://digitalcommons.calpoly.edu/theses/2464","outbound_label":"Repository record","outbound_source":"dc:identifier"},"metadata_groups":[{"id":"people","label":"People","entries":[{"key":"dc:contributor","label":"Contributor","values":["Wayne Pilkington","Electrical Engineering","College of Engineering"]},{"key":"dc:creator","label":"Author","values":["Chookaszian, Hannah Eileen"]}]},{"id":"academic_context","label":"Academic Context","entries":[{"key":"dc:date.available","label":"Dc Date Available","values":["2022-06-08T07:00:00Z"]},{"key":"thesis:degree_discipline","label":"Discipline","values":["Electrical Engineering"]},{"key":"thesis:degree_name","label":"Degree Name","values":["MS in Electrical Engineering"]}]},{"id":"subjects_keywords","label":"Subjects and Keywords","entries":[{"key":"dc:subject","label":"Dc Subject","values":["Digital Signals Processing","Music Information Retrieval","Music Source Separation","Music Information Visualization","Signal Processing"]}]},{"id":"identifiers","label":"Identifiers","entries":[{"key":"dc:identifier","label":"Identifier","values":["https://digitalcommons.calpoly.edu/theses/2464","10.15368/theses.2022.44"]}]},{"id":"additional","label":"Additional Metadata","entries":[{"key":"dc:description.abstract","label":"Abstract","values":["This thesis introduces a music visualization system for stereophonic source separated music. Music visualization systems are a popular way to represent information from audio signals through computer graphics. Visualization can help people better understand music and its complex and interacting elements. This music visualization system extracts pitch, panning, and loudness features from source separated audio files to create the visual. Most state-of-the art visualization systems develop their visual representation of the music from either the fully mixed final song recording, where all of the instruments and vocals are combined into one file, or from the digital audio workstation (DAW) data containing multiple independent recordings of individual audio sources. Original source recordings are not always readily available to the public so music source separation (MSS) can be used to obtain estimated versions of the audio source files. This thesis surveys different approaches to MSS and music visualization as well as introduces a new music visualization system specifically for source separated music.
"]},{"key":"dc:title","label":"Title","values":["Music Visualization Using Source Separated Stereophonic Music"]}]}],"canonical_facts":{"dc:contributor":["Wayne Pilkington","Electrical Engineering","College of Engineering"],"dc:creator":["Chookaszian, Hannah Eileen"],"dc:date.available":["2022-06-08T07:00:00Z"],"dc:description.abstract":["This thesis introduces a music visualization system for stereophonic source separated music. Music visualization systems are a popular way to represent information from audio signals through computer graphics. Visualization can help people better understand music and its complex and interacting elements. This music visualization system extracts pitch, panning, and loudness features from source separated audio files to create the visual. Most state-of-the art visualization systems develop their visual representation of the music from either the fully mixed final song recording, where all of the instruments and vocals are combined into one file, or from the digital audio workstation (DAW) data containing multiple independent recordings of individual audio sources. Original source recordings are not always readily available to the public so music source separation (MSS) can be used to obtain estimated versions of the audio source files. This thesis surveys different approaches to MSS and music visualization as well as introduces a new music visualization system specifically for source separated music.
"],"dc:identifier":["https://digitalcommons.calpoly.edu/theses/2464","10.15368/theses.2022.44"],"dc:subject":["Digital Signals Processing","Music Information Retrieval","Music Source Separation","Music Information Visualization","Signal Processing"],"dc:title":["Music Visualization Using Source Separated Stereophonic Music"],"thesis:degree_discipline":["Electrical Engineering"],"thesis:degree_name":["MS in Electrical Engineering"]},"updated_at":"2026-07-24T01:32:13Z"}