{"id":"https://openalex.org/W4221148459","doi":"https://doi.org/10.1109/taslp.2022.3231714","title":"Exploiting Low-Rank Tensor-Train Deep Neural Networks Based on Riemannian Gradient Descent With Illustrations of Speech Processing","display_name":"Exploiting Low-Rank Tensor-Train Deep Neural Networks Based on Riemannian Gradient Descent With Illustrations of Speech Processing","publication_year":2023,"publication_date":"2023-01-01","ids":{"openalex":"https://openalex.org/W4221148459","doi":"https://doi.org/10.1109/taslp.2022.3231714"},"language":"en","primary_location":{"id":"doi:10.1109/taslp.2022.3231714","is_oa":false,"landing_page_url":"https://doi.org/10.1109/taslp.2022.3231714","pdf_url":null,"source":{"id":"https://openalex.org/S4210169297","display_name":"IEEE/ACM Transactions on Audio Speech and Language Processing","issn_l":"2329-9290","issn":["2329-9290","2329-9304"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE/ACM Transactions on Audio, Speech, and Language Processing","raw_type":"journal-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":false,"oa_status":"closed","oa_url":null,"any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5042520842","display_name":"Jun Qi","orcid":"https://orcid.org/0000-0001-7533-2630"},"institutions":[{"id":"https://openalex.org/I130701444","display_name":"Georgia Institute of Technology","ror":"https://ror.org/01zkghx44","country_code":"US","type":"education","lineage":["https://openalex.org/I130701444"]},{"id":"https://openalex.org/I24943067","display_name":"Fudan University","ror":"https://ror.org/013q1eq08","country_code":"CN","type":"education","lineage":["https://openalex.org/I24943067"]}],"countries":["CN","US"],"is_corresponding":false,"raw_author_name":"Jun Qi","raw_affiliation_strings":["Department of Electronic Engineering, School of Information Science and Engineering, Fudan University, Shanghai, China","School of Electrical and Computer Engineering, Georgia Institute of Technology, Atlanta, GA, USA"],"raw_orcid":"https://orcid.org/0000-0001-7533-2630","affiliations":[{"raw_affiliation_string":"Department of Electronic Engineering, School of Information Science and Engineering, Fudan University, Shanghai, China","institution_ids":["https://openalex.org/I24943067"]},{"raw_affiliation_string":"School of Electrical and Computer Engineering, Georgia Institute of Technology, Atlanta, GA, USA","institution_ids":["https://openalex.org/I130701444"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5020376803","display_name":"Chao-Han Huck Yang","orcid":"https://orcid.org/0000-0003-2879-8811"},"institutions":[{"id":"https://openalex.org/I130701444","display_name":"Georgia Institute of Technology","ror":"https://ror.org/01zkghx44","country_code":"US","type":"education","lineage":["https://openalex.org/I130701444"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Chao-Han Huck Yang","raw_affiliation_strings":["School of Electrical and Computer Engineering, Georgia Institute of Technology, Atlanta, GA, USA"],"raw_orcid":"https://orcid.org/0000-0003-2879-8811","affiliations":[{"raw_affiliation_string":"School of Electrical and Computer Engineering, Georgia Institute of Technology, Atlanta, GA, USA","institution_ids":["https://openalex.org/I130701444"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5050344371","display_name":"Pin\u2010Yu Chen","orcid":"https://orcid.org/0000-0003-1039-8369"},"institutions":[{"id":"https://openalex.org/I1341412227","display_name":"IBM (United States)","ror":"https://ror.org/05hh8d621","country_code":"US","type":"company","lineage":["https://openalex.org/I1341412227"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Pin-Yu Chen","raw_affiliation_strings":["IBM Research, Yorktown Height, NY, USA"],"raw_orcid":"https://orcid.org/0000-0003-1039-8369","affiliations":[{"raw_affiliation_string":"IBM Research, Yorktown Height, NY, USA","institution_ids":["https://openalex.org/I1341412227"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5047221036","display_name":"Javier Tejedor","orcid":"https://orcid.org/0000-0001-7699-5620"},"institutions":[{"id":"https://openalex.org/I118091203","display_name":"Universidad San Pablo CEU","ror":"https://ror.org/00tvate34","country_code":"ES","type":"education","lineage":["https://openalex.org/I118091203","https://openalex.org/I2801318690"]}],"countries":["ES"],"is_corresponding":false,"raw_author_name":"Javier Tejedor","raw_affiliation_strings":["Institute of Technology, Universidad San Pablo-CEU, CEU Universities, Urbanizaci&#x00F3;n Montepr&#x00ED;ncipe, Boadilla del Monte, Spain"],"raw_orcid":"https://orcid.org/0000-0001-7699-5620","affiliations":[{"raw_affiliation_string":"Institute of Technology, Universidad San Pablo-CEU, CEU Universities, Urbanizaci&#x00F3;n Montepr&#x00ED;ncipe, Boadilla del Monte, Spain","institution_ids":["https://openalex.org/I118091203"]}]}],"institutions":[],"countries_distinct_count":3,"institutions_distinct_count":4,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":2.8715,"has_fulltext":false,"cited_by_count":15,"citation_normalized_percentile":{"value":0.91646489,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":94,"max":99},"biblio":{"volume":"31","issue":null,"first_page":"633","last_page":"642"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12303","display_name":"Tensor decomposition and applications","score":0.9994000196456909,"subfield":{"id":"https://openalex.org/subfields/2605","display_name":"Computational Mathematics"},"field":{"id":"https://openalex.org/fields/26","display_name":"Mathematics"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T12303","display_name":"Tensor decomposition and applications","score":0.9994000196456909,"subfield":{"id":"https://openalex.org/subfields/2605","display_name":"Computational Mathematics"},"field":{"id":"https://openalex.org/fields/26","display_name":"Mathematics"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T10860","display_name":"Speech and Audio Processing","score":0.9696999788284302,"subfield":{"id":"https://openalex.org/subfields/1711","display_name":"Signal Processing"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T11206","display_name":"Model Reduction and Neural Networks","score":0.9689000248908997,"subfield":{"id":"https://openalex.org/subfields/3109","display_name":"Statistical and Nonlinear Physics"},"field":{"id":"https://openalex.org/fields/31","display_name":"Physics and Astronomy"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.7435351610183716},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.652896523475647},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.5543696284294128},{"id":"https://openalex.org/keywords/leverage","display_name":"Leverage (statistics)","score":0.5434756875038147},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5347885489463806},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.486023485660553},{"id":"https://openalex.org/keywords/tensor","display_name":"Tensor (intrinsic definition)","score":0.46862342953681946},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.3979816138744354},{"id":"https://openalex.org/keywords/speech-recognition","display_name":"Speech recognition","score":0.3884945511817932},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.19726726412773132}],"concepts":[{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.7435351610183716},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.652896523475647},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.5543696284294128},{"id":"https://openalex.org/C153083717","wikidata":"https://www.wikidata.org/wiki/Q6535263","display_name":"Leverage (statistics)","level":2,"score":0.5434756875038147},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5347885489463806},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.486023485660553},{"id":"https://openalex.org/C155281189","wikidata":"https://www.wikidata.org/wiki/Q3518150","display_name":"Tensor (intrinsic definition)","level":2,"score":0.46862342953681946},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.3979816138744354},{"id":"https://openalex.org/C28490314","wikidata":"https://www.wikidata.org/wiki/Q189436","display_name":"Speech recognition","level":1,"score":0.3884945511817932},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.19726726412773132},{"id":"https://openalex.org/C202444582","wikidata":"https://www.wikidata.org/wiki/Q837863","display_name":"Pure mathematics","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/taslp.2022.3231714","is_oa":false,"landing_page_url":"https://doi.org/10.1109/taslp.2022.3231714","pdf_url":null,"source":{"id":"https://openalex.org/S4210169297","display_name":"IEEE/ACM Transactions on Audio Speech and Language Processing","issn_l":"2329-9290","issn":["2329-9290","2329-9304"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE/ACM Transactions on Audio, Speech, and Language Processing","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":56,"referenced_works":["https://openalex.org/W1531177993","https://openalex.org/W1552314771","https://openalex.org/W1560013842","https://openalex.org/W1887381766","https://openalex.org/W1902237438","https://openalex.org/W1982067089","https://openalex.org/W1985744509","https://openalex.org/W1993482030","https://openalex.org/W2001964924","https://openalex.org/W2024165284","https://openalex.org/W2033368244","https://openalex.org/W2039240409","https://openalex.org/W2057498692","https://openalex.org/W2063385922","https://openalex.org/W2067295501","https://openalex.org/W2102148524","https://openalex.org/W2117852776","https://openalex.org/W2138196899","https://openalex.org/W2138674039","https://openalex.org/W2168013545","https://openalex.org/W2194775991","https://openalex.org/W2469230926","https://openalex.org/W2514828952","https://openalex.org/W2765507192","https://openalex.org/W2765932895","https://openalex.org/W2773126525","https://openalex.org/W2797583228","https://openalex.org/W2888641632","https://openalex.org/W2969649301","https://openalex.org/W3022073510","https://openalex.org/W3049226960","https://openalex.org/W3096509852","https://openalex.org/W3098805155","https://openalex.org/W3102317997","https://openalex.org/W3135536164","https://openalex.org/W3161932608","https://openalex.org/W3205418336","https://openalex.org/W4225319303","https://openalex.org/W4245919820","https://openalex.org/W6631190155","https://openalex.org/W6638060716","https://openalex.org/W6729295261","https://openalex.org/W6730093588","https://openalex.org/W6741042017","https://openalex.org/W6745148473","https://openalex.org/W6745397846","https://openalex.org/W6745544366","https://openalex.org/W6746012787","https://openalex.org/W6750665317","https://openalex.org/W6751420435","https://openalex.org/W6752343131","https://openalex.org/W6755310813","https://openalex.org/W6755843862","https://openalex.org/W6773423997","https://openalex.org/W6773951132","https://openalex.org/W7062452349"],"related_works":["https://openalex.org/W4312417841","https://openalex.org/W4321369474","https://openalex.org/W2731899572","https://openalex.org/W3133861977","https://openalex.org/W4200173597","https://openalex.org/W3116150086","https://openalex.org/W2999805992","https://openalex.org/W4291897433","https://openalex.org/W3011074480","https://openalex.org/W3192840557"],"abstract_inverted_index":{"This":[0],"work":[1],"focuses":[2],"on":[3,116],"designing":[4],"low-complexity":[5],"hybrid":[6,40],"tensor":[7],"networks":[8],"by":[9],"considering":[10],"trade-offs":[11],"between":[12],"the":[13,60,90,100,111,129,140],"model":[14,41,136],"complexity":[15],"and":[16,95,105,113,119,131,142],"practical":[17],"performance.":[18,61],"Firstly,":[19],"we":[20,70],"exploit":[21],"a":[22,39,45,77],"low-rank":[23],"tensor-train":[24],"deep":[25,33],"neural":[26,47],"network":[27,48],"(TT-DNN)":[28],"to":[29,58,75,102],"build":[30],"an":[31],"end-to-end":[32],"learning":[34],"pipeline,":[35],"namely":[36],"LR-TT-DNN.":[37],"Secondly,":[38],"combining":[42],"LR-TT-DNN":[43,112,130],"with":[44,80,134],"convolutional":[46,87],"(CNN),":[49],"which":[50],"is":[51,55],"denoted":[52],"as":[53],"CNN+(LR-TT-DNN),":[54],"set":[56],"up":[57],"boost":[59],"Instead":[62],"of":[63,86],"randomly":[64],"assigning":[65],"large":[66],"TT-ranks":[67],"for":[68,92],"TT-DNN,":[69],"leverage":[71],"Riemannian":[72],"gradient":[73],"descent":[74],"determine":[76],"TT-DNN":[78,141],"associated":[79],"small":[81],"TT-ranks.":[82],"Furthermore,":[83],"CNN+(LR-TT-DNN)":[84,114,132],"consists":[85],"layers":[88,98],"at":[89,99],"bottom":[91],"feature":[93],"extraction":[94],"several":[96],"TT":[97],"top":[101],"solve":[103],"regression":[104],"classification":[106],"problems.":[107],"We":[108],"separately":[109],"assess":[110],"models":[115,133],"speech":[117],"enhancement":[118],"spoken":[120],"command":[121],"recognition":[122],"tasks.":[123],"Our":[124],"empirical":[125],"evidence":[126],"demonstrates":[127],"that":[128],"fewer":[135],"parameters":[137],"can":[138],"outperform":[139],"CNN+(TT-DNN)":[143],"counterparts.":[144]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":6},{"year":2024,"cited_by_count":4},{"year":2023,"cited_by_count":4}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
