{"id":{"repo_id":"uiuc","oai_identifier":"oai:www.ideals.illinois.edu:2142/127217"},"canonical_url":"https://search.dev.ndltd.org/etd/uiuc/oai:www.ideals.illinois.edu:2142/127217","repository":{"repo_id":"uiuc","name":"University of Illinois - Urbana-Champaign","base_url":"https://www.ideals.illinois.edu/oai-pmh"},"display":{"title":"Automating acoustic signal processing experiments and audio machine learning datasets using robots","abstract":"Submission original under an indefinite embargo labeled 'Open Access'. The submission was exported from vireo on 2025-03-28 without embargo terms","abstract_html":"Submission original under an indefinite embargo labeled 'Open Access'. The submission was exported from vireo on 2025-03-28 without embargo terms","abstract_has_math":false,"creators":["Lu, Austin"],"institution":"University of Illinois at Urbana-Champaign","degree_name":"M.S.","degree_level":"Thesis","degree_discipline":"Electrical & Computer Engr","degree_department":null,"school":null,"contributors":["Singer, Andrew C","Corey, Ryan M"],"advisors":[],"committee_chairs":[],"committee_members":[],"year":2024,"date_issued":"2024-12-11","date_published":"2024-12-11","updated_at":"2026-07-22T22:25:03Z","subjects":["Audio Signal Processing","Microphone Arrays","Spatial Audio","Robotics","3d Printing"],"languages":["en","eng"],"rights":["Copyright 2024 Austin Lu"],"rights_urls":[],"identifier_entries":[]},"links":{"outbound_url":"https://hdl.handle.net/2142/127217","outbound_label":"Handle","outbound_source":"dc:identifier"},"metadata_groups":[{"id":"people","label":"People","entries":[{"key":"dc:contributor","label":"Contributor","values":["Singer, Andrew C","Corey, Ryan M"]},{"key":"dc:creator","label":"Author","values":["Lu, Austin"]}]},{"id":"academic_context","label":"Academic Context","entries":[{"key":"dc:date","label":"Dc Date","values":["2024-12-11","2024-12"]},{"key":"dc:type","label":"Dc Type","values":["text","Thesis"]},{"key":"thesis:degree_discipline","label":"Discipline","values":["Electrical & Computer Engr"]},{"key":"thesis:degree_level","label":"Degree Level","values":["Thesis"]},{"key":"thesis:degree_name","label":"Degree Name","values":["M.S."]},{"key":"thesis:institution_name","label":"Thesis Institution Name","values":["University of Illinois at Urbana-Champaign"]}]},{"id":"subjects_keywords","label":"Subjects and Keywords","entries":[{"key":"dc:subject","label":"Dc Subject","values":["Audio Signal Processing","Microphone Arrays","Spatial Audio","Robotics","3d Printing"]}]},{"id":"language_rights","label":"Language and Rights","entries":[{"key":"dc:language","label":"Dc Language","values":["en","eng"]},{"key":"dc:rights","label":"Dc Rights","values":["Copyright 2024 Austin Lu"]}]},{"id":"identifiers","label":"Identifiers","entries":[{"key":"dc:identifier","label":"Identifier","values":["https://hdl.handle.net/2142/127217"]}]},{"id":"additional","label":"Additional Metadata","entries":[{"key":"dc:description","label":"Description","values":["Submission original under an indefinite embargo labeled 'Open Access'. The submission was exported from vireo on 2025-03-28 without embargo terms","The student, Austin Lu, accepted the attached license on 2024-12-10 at 16:41.","The student, Austin Lu, submitted this Thesis for approval on 2024-12-10 at 17:00.","This Thesis was approved for publication on 2024-12-11 at 16:06.","DSpace SAF Submission Ingestion Package generated from Vireo submission #21383 on 2025-03-28 at 14:26:03","We develop specialized robots for audio and acoustic experiments, which in turn facilitate acoustic signal processing and audio machine learning. Our robo-acoustic mannequin, a low-cost 3D printed device, is custom-made to enable interesting spatially-dynamic experiments. We explore simple solutions to quiet actuation, thus avoiding the infamous problem of audible robot noise, and we open-source our design to stimulate further development. Using this new research resource, we empirically study how motion, specifically head-turning, affects the objective performance of a spatially-adaptive MVDR beamformer. We find the surprising result that the presence of motion has a significant effect, but the rate of motion does not. To study more intricate scenarios, we also design a multi-robot mechatronic recording studio that automatically captures high-resolution labeled audio datasets. Large-scale multiple-day-spanning recordings that would be impossible to do manually become possible through this work. The multi-robot system is accessed by geographically disparate researchers via a “DAW for robots” web interface, thus demonstrating the potential of shared, collaborative audio-robot workspaces. Overall, we expect our work to motivate new and interesting robot-enhanced audio experiments and datasets."]},{"key":"dc:format","label":"Dc Format","values":["application/pdf"]},{"key":"dc:title","label":"Title","values":["Automating acoustic signal processing experiments and audio machine learning datasets using robots"]}]}],"canonical_facts":{"dc:contributor":["Singer, Andrew C","Corey, Ryan M"],"dc:creator":["Lu, Austin"],"dc:date":["2024-12-11","2024-12"],"dc:description":["Submission original under an indefinite embargo labeled 'Open Access'. The submission was exported from vireo on 2025-03-28 without embargo terms","The student, Austin Lu, accepted the attached license on 2024-12-10 at 16:41.","The student, Austin Lu, submitted this Thesis for approval on 2024-12-10 at 17:00.","This Thesis was approved for publication on 2024-12-11 at 16:06.","DSpace SAF Submission Ingestion Package generated from Vireo submission #21383 on 2025-03-28 at 14:26:03","We develop specialized robots for audio and acoustic experiments, which in turn facilitate acoustic signal processing and audio machine learning. Our robo-acoustic mannequin, a low-cost 3D printed device, is custom-made to enable interesting spatially-dynamic experiments. We explore simple solutions to quiet actuation, thus avoiding the infamous problem of audible robot noise, and we open-source our design to stimulate further development. Using this new research resource, we empirically study how motion, specifically head-turning, affects the objective performance of a spatially-adaptive MVDR beamformer. We find the surprising result that the presence of motion has a significant effect, but the rate of motion does not. To study more intricate scenarios, we also design a multi-robot mechatronic recording studio that automatically captures high-resolution labeled audio datasets. Large-scale multiple-day-spanning recordings that would be impossible to do manually become possible through this work. The multi-robot system is accessed by geographically disparate researchers via a “DAW for robots” web interface, thus demonstrating the potential of shared, collaborative audio-robot workspaces. Overall, we expect our work to motivate new and interesting robot-enhanced audio experiments and datasets."],"dc:format":["application/pdf"],"dc:identifier":["https://hdl.handle.net/2142/127217"],"dc:language":["en","eng"],"dc:rights":["Copyright 2024 Austin Lu"],"dc:subject":["Audio Signal Processing","Microphone Arrays","Spatial Audio","Robotics","3d Printing"],"dc:title":["Automating acoustic signal processing experiments and audio machine learning datasets using robots"],"dc:type":["text","Thesis"],"thesis:degree_discipline":["Electrical & Computer Engr"],"thesis:degree_level":["Thesis"],"thesis:degree_name":["M.S."],"thesis:institution_name":["University of Illinois at Urbana-Champaign"]},"updated_at":"2026-07-22T22:25:03Z"}