{"id":{"repo_id":"uiuc","oai_identifier":"oai:www.ideals.illinois.edu:2142/92668"},"canonical_url":"https://search.dev.ndltd.org/etd/uiuc/oai:www.ideals.illinois.edu:2142/92668","repository":{"repo_id":"uiuc","name":"University of Illinois - Urbana-Champaign","base_url":"https://www.ideals.illinois.edu/oai-pmh"},"display":{"title":"A high accuracy nonlinear model of the human cochlea","abstract":"Reliably modeling the human auditory system is of fundamental importance to audio processing systems and hearing research. Generally, models intended for real-time audio processing are time-efficient but tend to lack grounding in physical reality, while models designed for hearing research may closely fit experimental data but cannot always be meaningfully applied in audio processing situations. The goal of this research is to design a computational model of the human auditory system which manages the trade-off between physical correctness and audio processing practicality. The proposed model is a bank of nonlinear digital filters followed by models of the outer and inner hair cells. Methods are introduced which allow for convex optimization of the parameters of the nonlinear filter bank to fit frequency responses generated by a high-accuracy physical model of the auditory system (the Sen-Allen model). Further optimization methods are introduced which fit the parameters of the hair cell models using experimental data on the basilar membrane compression curve and the intensity just-noticeable-difference. The result is an efficient multi-rate system which can be easily reconfigured based on the needs of the application. Preliminary tests of the model show that it is capable of reproducing documented psychoacoustical effects such as pure tone forward and simultaneous masking. Furthermore, an audibility prediction system based on the model is developed and compared to the state-of-the-art articulation index gram. After a brief investigation, the novel system (termed the cochlear voltage difference gram) seems to predict the audibility of speech cues in noise as well as or better than the articulation index gram in most cases, although a thorough comparative analysis must still be conducted. At a 16 [kHz] sampling rate, simulating 100 frequency channels on the cochlea, a Matlab implementation of the model runs about half as fast as real time. Due to the highly parallel nature of the model, it is expected that a similar implementation on a digital signal processor or graphics processing unit could be optimized to run in real time.","abstract_html":"Reliably modeling the human auditory system is of fundamental importance to audio processing systems and hearing research. Generally, models intended for real-time audio processing are time-efficient but tend to lack grounding in physical reality, while models designed for hearing research may closely fit experimental data but cannot always be meaningfully applied in audio processing situations. The goal of this research is to design a computational model of the human auditory system which manages the trade-off between physical correctness and audio processing practicality. The proposed model is a bank of nonlinear digital filters followed by models of the outer and inner hair cells. Methods are introduced which allow for convex optimization of the parameters of the nonlinear filter bank to fit frequency responses generated by a high-accuracy physical model of the auditory system (the Sen-Allen model). Further optimization methods are introduced which fit the parameters of the hair cell models using experimental data on the basilar membrane compression curve and the intensity just-noticeable-difference. The result is an efficient multi-rate system which can be easily reconfigured based on the needs of the application. Preliminary tests of the model show that it is capable of reproducing documented psychoacoustical effects such as pure tone forward and simultaneous masking. Furthermore, an audibility prediction system based on the model is developed and compared to the state-of-the-art articulation index gram. After a brief investigation, the novel system (termed the cochlear voltage difference gram) seems to predict the audibility of speech cues in noise as well as or better than the articulation index gram in most cases, although a thorough comparative analysis must still be conducted. At a 16 [kHz] sampling rate, simulating 100 frequency channels on the cochlea, a Matlab implementation of the model runs about half as fast as real time. Due to the highly parallel nature of the model, it is expected that a similar implementation on a digital signal processor or graphics processing unit could be optimized to run in real time.","abstract_has_math":false,"creators":["Sullivan, Christopher L"],"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":["Allen, Jont B."],"advisors":[],"committee_chairs":[],"committee_members":[],"year":2016,"date_issued":"2016-11-10T17:49:12Z","date_published":"2016-11-10T17:49:12Z","updated_at":"2026-07-22T22:26:35Z","subjects":["cochlear modeling","signal processing","filter fitting","resonant tectorial membrane","audibility","speech perception"],"languages":["en"],"rights":["Copyright 2016 Christopher L. Sullivan. All rights reserved."],"rights_urls":[],"identifier_entries":[]},"links":{"outbound_url":"http://hdl.handle.net/2142/92668","outbound_label":"Handle","outbound_source":"dc:identifier"},"metadata_groups":[{"id":"people","label":"People","entries":[{"key":"dc:contributor","label":"Contributor","values":["Allen, Jont B."]},{"key":"dc:creator","label":"Author","values":["Sullivan, Christopher L"]}]},{"id":"academic_context","label":"Academic Context","entries":[{"key":"dc:date","label":"Dc Date","values":["2016-11-10T17:49:12Z","2016-07-21","2016-08"]},{"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":["cochlear modeling","signal processing","filter fitting","resonant tectorial membrane","audibility","speech perception"]}]},{"id":"language_rights","label":"Language and Rights","entries":[{"key":"dc:language","label":"Dc Language","values":["en"]},{"key":"dc:rights","label":"Dc Rights","values":["Copyright 2016 Christopher L. Sullivan. All rights reserved."]}]},{"id":"identifiers","label":"Identifiers","entries":[{"key":"dc:identifier","label":"Identifier","values":["http://hdl.handle.net/2142/92668"]}]},{"id":"additional","label":"Additional Metadata","entries":[{"key":"dc:description","label":"Description","values":["Reliably modeling the human auditory system is of fundamental importance to audio processing systems and hearing research. Generally, models intended for real-time audio processing are time-efficient but tend to lack grounding in physical reality, while models designed for hearing research may closely fit experimental data but cannot always be meaningfully applied in audio processing situations. The goal of this research is to design a computational model of the human auditory system which manages the trade-off between physical correctness and audio processing practicality. The proposed model is a bank of nonlinear digital filters followed by models of the outer and inner hair cells. Methods are introduced which allow for convex optimization of the parameters of the nonlinear filter bank to fit frequency responses generated by a high-accuracy physical model of the auditory system (the Sen-Allen model). Further optimization methods are introduced which fit the parameters of the hair cell models using experimental data on the basilar membrane compression curve and the intensity just-noticeable-difference. The result is an efficient multi-rate system which can be easily reconfigured based on the needs of the application. Preliminary tests of the model show that it is capable of reproducing documented psychoacoustical effects such as pure tone forward and simultaneous masking. Furthermore, an audibility prediction system based on the model is developed and compared to the state-of-the-art articulation index gram. After a brief investigation, the novel system (termed the cochlear voltage difference gram) seems to predict the audibility of speech cues in noise as well as or better than the articulation index gram in most cases, although a thorough comparative analysis must still be conducted. At a 16 [kHz] sampling rate, simulating 100 frequency channels on the cochlea, a Matlab implementation of the model runs about half as fast as real time. Due to the highly parallel nature of the model, it is expected that a similar implementation on a digital signal processor or graphics processing unit could be optimized to run in real time.","Submission original under an indefinite embargo labeled 'Open Access'. The submission was exported from vireo on 2016-11-09 without embargo terms","The student, Christopher Sullivan, accepted the attached license on 2016-07-20 at 16:22.","The student, Christopher Sullivan, submitted this Thesis for approval on 2016-07-20 at 16:33.","This Thesis was approved for publication on 2016-07-21 at 09:09.","DSpace SAF Submission Ingestion Package generated from Vireo submission #10041 on 2016-11-09 at 10:25:59","Made available in DSpace on 2016-11-10T17:49:12Z (GMT). No. of bitstreams: 2 SULLIVAN-THESIS-2016.pdf: 1686919 bytes, checksum: ed0ec805e0553d55db4ecfb55eb5319f (MD5) LICENSE.txt: 4217 bytes, checksum: 32487c8af902ccc78839f2ecf321c5e9 (MD5) Previous issue date: 2016-07-21"]},{"key":"dc:format","label":"Dc Format","values":["application/pdf"]},{"key":"dc:title","label":"Title","values":["A high accuracy nonlinear model of the human cochlea"]}]}],"canonical_facts":{"dc:contributor":["Allen, Jont B."],"dc:creator":["Sullivan, Christopher L"],"dc:date":["2016-11-10T17:49:12Z","2016-07-21","2016-08"],"dc:description":["Reliably modeling the human auditory system is of fundamental importance to audio processing systems and hearing research. Generally, models intended for real-time audio processing are time-efficient but tend to lack grounding in physical reality, while models designed for hearing research may closely fit experimental data but cannot always be meaningfully applied in audio processing situations. The goal of this research is to design a computational model of the human auditory system which manages the trade-off between physical correctness and audio processing practicality. The proposed model is a bank of nonlinear digital filters followed by models of the outer and inner hair cells. Methods are introduced which allow for convex optimization of the parameters of the nonlinear filter bank to fit frequency responses generated by a high-accuracy physical model of the auditory system (the Sen-Allen model). Further optimization methods are introduced which fit the parameters of the hair cell models using experimental data on the basilar membrane compression curve and the intensity just-noticeable-difference. The result is an efficient multi-rate system which can be easily reconfigured based on the needs of the application. Preliminary tests of the model show that it is capable of reproducing documented psychoacoustical effects such as pure tone forward and simultaneous masking. Furthermore, an audibility prediction system based on the model is developed and compared to the state-of-the-art articulation index gram. After a brief investigation, the novel system (termed the cochlear voltage difference gram) seems to predict the audibility of speech cues in noise as well as or better than the articulation index gram in most cases, although a thorough comparative analysis must still be conducted. At a 16 [kHz] sampling rate, simulating 100 frequency channels on the cochlea, a Matlab implementation of the model runs about half as fast as real time. Due to the highly parallel nature of the model, it is expected that a similar implementation on a digital signal processor or graphics processing unit could be optimized to run in real time.","Submission original under an indefinite embargo labeled 'Open Access'. The submission was exported from vireo on 2016-11-09 without embargo terms","The student, Christopher Sullivan, accepted the attached license on 2016-07-20 at 16:22.","The student, Christopher Sullivan, submitted this Thesis for approval on 2016-07-20 at 16:33.","This Thesis was approved for publication on 2016-07-21 at 09:09.","DSpace SAF Submission Ingestion Package generated from Vireo submission #10041 on 2016-11-09 at 10:25:59","Made available in DSpace on 2016-11-10T17:49:12Z (GMT). No. of bitstreams: 2 SULLIVAN-THESIS-2016.pdf: 1686919 bytes, checksum: ed0ec805e0553d55db4ecfb55eb5319f (MD5) LICENSE.txt: 4217 bytes, checksum: 32487c8af902ccc78839f2ecf321c5e9 (MD5) Previous issue date: 2016-07-21"],"dc:format":["application/pdf"],"dc:identifier":["http://hdl.handle.net/2142/92668"],"dc:language":["en"],"dc:rights":["Copyright 2016 Christopher L. Sullivan. All rights reserved."],"dc:subject":["cochlear modeling","signal processing","filter fitting","resonant tectorial membrane","audibility","speech perception"],"dc:title":["A high accuracy nonlinear model of the human cochlea"],"dc:type":["text"],"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":"2026-07-22T22:26:35Z"}