{"id":{"repo_id":"uiuc","oai_identifier":"oai:www.ideals.illinois.edu:2142/105262"},"canonical_url":"https://search.dev.ndltd.org/etd/uiuc/oai:www.ideals.illinois.edu:2142/105262","repository":{"repo_id":"uiuc","name":"University of Illinois - Urbana-Champaign","base_url":"https://www.ideals.illinois.edu/oai-pmh"},"display":{"title":"Source localization from voice signals","abstract":"Indoor localization remains an open field of research, due to its utility and unresolved challenges. This thesis focuses on sound source localization using a small microphone array. Practically speaking, the aim is to allow smart voice assistants, such as Amazon Echo or Google Home, which possess a small array of microphones, to locate human speakers by determining the location of their voice in space. Although such voice assistants are currently capable of determining the azimuthal angle of arrival (AoA) of the human voice, they cannot determine the range of the speaker. This thesis addresses the two-dimensional localization problem: when a user speaks to an Amazon Echo, our goal is to be able to plot their location as a point on a bird’s eye view of the indoor floorplan. Our proposed solution, VoLoc, realizes two-dimensional sound source localization by determining the AoA of not only the direct path, but also one multipath. With two AoA directions, VoLoc is able to use inverse ray-tracing to find the sound source’s location in 2D space. One of the core challenges is to accurately distinguish the AoA of at least one multipath. To address the challenge, we introduce a new algorithm, iterative align-and-cancel. We observe median location accuracies of around 0.4m, across various real-world environments such as apartments, offices, and meeting rooms.","abstract_html":"Indoor localization remains an open field of research, due to its utility and unresolved challenges. This thesis focuses on sound source localization using a small microphone array. Practically speaking, the aim is to allow smart voice assistants, such as Amazon Echo or Google Home, which possess a small array of microphones, to locate human speakers by determining the location of their voice in space. Although such voice assistants are currently capable of determining the azimuthal angle of arrival (AoA) of the human voice, they cannot determine the range of the speaker. This thesis addresses the two-dimensional localization problem: when a user speaks to an Amazon Echo, our goal is to be able to plot their location as a point on a bird’s eye view of the indoor floorplan. Our proposed solution, VoLoc, realizes two-dimensional sound source localization by determining the AoA of not only the direct path, but also one multipath. With two AoA directions, VoLoc is able to use inverse ray-tracing to find the sound source’s location in 2D space. One of the core challenges is to accurately distinguish the AoA of at least one multipath. To address the challenge, we introduce a new algorithm, iterative align-and-cancel. We observe median location accuracies of around 0.4m, across various real-world environments such as apartments, offices, and meeting rooms.","abstract_has_math":false,"creators":["Chen, Daguan"],"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":["Choudhury, Romit Roy"],"advisors":[],"committee_chairs":[],"committee_members":[],"year":2019,"date_issued":"2019-08-23T20:48:26Z","date_published":"2019-08-23T20:48:26Z","updated_at":"2026-07-22T22:24:44Z","subjects":["Sound","localization","microphone array","AoA","sound source localization"],"languages":["en"],"rights":["Copyright 2019 Daguan Chen"],"rights_urls":[],"identifier_entries":[]},"links":{"outbound_url":"http://hdl.handle.net/2142/105262","outbound_label":"Handle","outbound_source":"dc:identifier"},"metadata_groups":[{"id":"people","label":"People","entries":[{"key":"dc:contributor","label":"Contributor","values":["Choudhury, Romit Roy"]},{"key":"dc:creator","label":"Author","values":["Chen, Daguan"]}]},{"id":"academic_context","label":"Academic Context","entries":[{"key":"dc:date","label":"Dc Date","values":["2019-08-23T20:48:26Z","2021-08-24T09:15:20Z","2019-04-24","2019-05"]},{"key":"dc:type","label":"Dc Type","values":["text"]},{"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":["Sound","localization","microphone array","AoA","sound source localization"]}]},{"id":"language_rights","label":"Language and Rights","entries":[{"key":"dc:language","label":"Dc Language","values":["en"]},{"key":"dc:rights","label":"Dc Rights","values":["Copyright 2019 Daguan Chen"]}]},{"id":"identifiers","label":"Identifiers","entries":[{"key":"dc:identifier","label":"Identifier","values":["http://hdl.handle.net/2142/105262"]}]},{"id":"additional","label":"Additional Metadata","entries":[{"key":"dc:description","label":"Description","values":["Indoor localization remains an open field of research, due to its utility and unresolved challenges. This thesis focuses on sound source localization using a small microphone array. Practically speaking, the aim is to allow smart voice assistants, such as Amazon Echo or Google Home, which possess a small array of microphones, to locate human speakers by determining the location of their voice in space. Although such voice assistants are currently capable of determining the azimuthal angle of arrival (AoA) of the human voice, they cannot determine the range of the speaker. This thesis addresses the two-dimensional localization problem: when a user speaks to an Amazon Echo, our goal is to be able to plot their location as a point on a bird’s eye view of the indoor floorplan. Our proposed solution, VoLoc, realizes two-dimensional sound source localization by determining the AoA of not only the direct path, but also one multipath. With two AoA directions, VoLoc is able to use inverse ray-tracing to find the sound source’s location in 2D space. One of the core challenges is to accurately distinguish the AoA of at least one multipath. To address the challenge, we introduce a new algorithm, iterative align-and-cancel. We observe median location accuracies of around 0.4m, across various real-world environments such as apartments, offices, and meeting rooms.","Submission published under a 24 month embargo labeled 'Closed Access', the embargo will last until 2021-05-01","The student, Daguan Chen, accepted the attached license on 2019-04-24 at 16:26.","The student, Daguan Chen, submitted this Thesis for approval on 2019-04-24 at 16:34.","This Thesis was approved for publication on 2019-04-24 at 17:53.","DSpace SAF Submission Ingestion Package generated from Vireo submission #13890 on 2019-08-22 at 16:23:52","Made available in DSpace on 2019-08-23T20:48:26Z (GMT). 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