{"id":"https://openalex.org/W2296483664","doi":"https://doi.org/10.21437/interspeech.2015-603","title":"Speaker adaptation using the i-vector technique for bottleneck features","display_name":"Speaker adaptation using the i-vector technique for bottleneck features","publication_year":2015,"publication_date":"2015-09-06","ids":{"openalex":"https://openalex.org/W2296483664","doi":"https://doi.org/10.21437/interspeech.2015-603","mag":"2296483664"},"language":"en","primary_location":{"id":"doi:10.21437/interspeech.2015-603","is_oa":false,"landing_page_url":"https://doi.org/10.21437/interspeech.2015-603","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Interspeech 2015","raw_type":"proceedings-article"},"type":"conference-paper","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/A5051056084","display_name":"Patrick Cardinal","orcid":"https://orcid.org/0009-0000-9439-9910"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Patrick Cardinal","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5050632169","display_name":"Najim Dehak","orcid":"https://orcid.org/0000-0002-4489-5753"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Najim Dehak","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100433691","display_name":"Yu Zhang","orcid":"https://orcid.org/0000-0003-1100-4835"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Yu Zhang","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5112758056","display_name":"James Glass","orcid":"https://orcid.org/0000-0002-3097-360X"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"James Glass","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":0,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":20,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"2867","last_page":"2871"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10201","display_name":"Speech Recognition and Synthesis","score":0.9998999834060669,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T10201","display_name":"Speech Recognition and Synthesis","score":0.9998999834060669,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"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/T10860","display_name":"Speech and Audio Processing","score":0.9962999820709229,"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/T11309","display_name":"Music and Audio Processing","score":0.9944999814033508,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/hidden-markov-model","display_name":"Hidden Markov model","score":0.8467082381248474},{"id":"https://openalex.org/keywords/speech-recognition","display_name":"Speech recognition","score":0.7858242392539978},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7648006677627563},{"id":"https://openalex.org/keywords/bottleneck","display_name":"Bottleneck","score":0.7074506878852844},{"id":"https://openalex.org/keywords/speaker-recognition","display_name":"Speaker recognition","score":0.6328526735305786},{"id":"https://openalex.org/keywords/context","display_name":"Context (archaeology)","score":0.5943452715873718},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5362958312034607},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.5083052515983582},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.5050252079963684},{"id":"https://openalex.org/keywords/mixture-model","display_name":"Mixture model","score":0.4503157138824463},{"id":"https://openalex.org/keywords/representation","display_name":"Representation (politics)","score":0.4309680759906769},{"id":"https://openalex.org/keywords/adaptation","display_name":"Adaptation (eye)","score":0.41469237208366394},{"id":"https://openalex.org/keywords/context-model","display_name":"Context model","score":0.4128163456916809}],"concepts":[{"id":"https://openalex.org/C23224414","wikidata":"https://www.wikidata.org/wiki/Q176769","display_name":"Hidden Markov model","level":2,"score":0.8467082381248474},{"id":"https://openalex.org/C28490314","wikidata":"https://www.wikidata.org/wiki/Q189436","display_name":"Speech recognition","level":1,"score":0.7858242392539978},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7648006677627563},{"id":"https://openalex.org/C2780513914","wikidata":"https://www.wikidata.org/wiki/Q18210350","display_name":"Bottleneck","level":2,"score":0.7074506878852844},{"id":"https://openalex.org/C133892786","wikidata":"https://www.wikidata.org/wiki/Q1145189","display_name":"Speaker recognition","level":2,"score":0.6328526735305786},{"id":"https://openalex.org/C2779343474","wikidata":"https://www.wikidata.org/wiki/Q3109175","display_name":"Context (archaeology)","level":2,"score":0.5943452715873718},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5362958312034607},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.5083052515983582},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.5050252079963684},{"id":"https://openalex.org/C61224824","wikidata":"https://www.wikidata.org/wiki/Q2260434","display_name":"Mixture model","level":2,"score":0.4503157138824463},{"id":"https://openalex.org/C2776359362","wikidata":"https://www.wikidata.org/wiki/Q2145286","display_name":"Representation (politics)","level":3,"score":0.4309680759906769},{"id":"https://openalex.org/C139807058","wikidata":"https://www.wikidata.org/wiki/Q352374","display_name":"Adaptation (eye)","level":2,"score":0.41469237208366394},{"id":"https://openalex.org/C183322885","wikidata":"https://www.wikidata.org/wiki/Q17007702","display_name":"Context model","level":3,"score":0.4128163456916809},{"id":"https://openalex.org/C151730666","wikidata":"https://www.wikidata.org/wiki/Q7205","display_name":"Paleontology","level":1,"score":0.0},{"id":"https://openalex.org/C199539241","wikidata":"https://www.wikidata.org/wiki/Q7748","display_name":"Law","level":1,"score":0.0},{"id":"https://openalex.org/C120665830","wikidata":"https://www.wikidata.org/wiki/Q14620","display_name":"Optics","level":1,"score":0.0},{"id":"https://openalex.org/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","level":0,"score":0.0},{"id":"https://openalex.org/C94625758","wikidata":"https://www.wikidata.org/wiki/Q7163","display_name":"Politics","level":2,"score":0.0},{"id":"https://openalex.org/C2781238097","wikidata":"https://www.wikidata.org/wiki/Q175026","display_name":"Object (grammar)","level":2,"score":0.0},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0},{"id":"https://openalex.org/C149635348","wikidata":"https://www.wikidata.org/wiki/Q193040","display_name":"Embedded system","level":1,"score":0.0},{"id":"https://openalex.org/C17744445","wikidata":"https://www.wikidata.org/wiki/Q36442","display_name":"Political science","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.21437/interspeech.2015-603","is_oa":false,"landing_page_url":"https://doi.org/10.21437/interspeech.2015-603","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Interspeech 2015","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":17,"referenced_works":["https://openalex.org/W82501063","https://openalex.org/W1989549063","https://openalex.org/W2002342963","https://openalex.org/W2058641082","https://openalex.org/W2079623482","https://openalex.org/W2090958120","https://openalex.org/W2105099419","https://openalex.org/W2123237149","https://openalex.org/W2124973918","https://openalex.org/W2150769028","https://openalex.org/W2155501171","https://openalex.org/W2189369791","https://openalex.org/W2251742274","https://openalex.org/W2277634955","https://openalex.org/W2397534874","https://openalex.org/W2398569491","https://openalex.org/W2400718301"],"related_works":["https://openalex.org/W4324119469","https://openalex.org/W2164868312","https://openalex.org/W2160650576","https://openalex.org/W1197719229","https://openalex.org/W2381158726","https://openalex.org/W1992796048","https://openalex.org/W1992908141","https://openalex.org/W2129090883","https://openalex.org/W1516392727","https://openalex.org/W2379906719"],"abstract_inverted_index":{"Deep":[0],"Neural":[1],"Networks":[2],"(DNN)":[3],"have":[4],"been":[5],"largely":[6],"used":[7],"and":[8],"successfully":[9],"applied":[10],"in":[11,83,113],"the":[12,47,53,59,65,70,84,103,110,114],"context":[13,85,115],"of":[14,45,61,86,90,105,116,127,148],"speaker":[15,32,66,106],"independent":[16],"Automatic":[17],"Speech":[18,162],"Recognition":[19,163],"(ASR).":[20],"However,":[21],"these":[22],"models":[23],"are":[24,129],"not":[25],"easily":[26],"adapted":[27],"to":[28,39,52],"model":[29],"a":[30,74,80,87,124,132],"specific":[31],"characteristic.":[33],"Recently,":[34],"one":[35],"approach":[36,78,142],"was":[37],"proposed":[38,141],"address":[40],"this":[41,99],"issue,":[42],"which":[43],"consists":[44],"using":[46],"I-vector":[48,56,111],"representation":[49],"as":[50,67,69],"input":[51],"DNN.":[54],"The":[55,140],"is":[57],"playing":[58],"role":[60],"providing":[62],"information":[63],"about":[64],"well":[68],"environmental":[71],"conditions":[72],"for":[73],"given":[75],"recording.":[76],"This":[77],"achieved":[79,143],"significant":[81],"improvement":[82,147],"hybrid":[88],"system":[89],"DNN":[91],"combined":[92],"with":[93],"Hidden":[94],"Markov":[95],"Model":[96,136],"(HMM).":[97],"In":[98],"paper,":[100],"we":[101],"study":[102],"effect":[104],"adaptation":[107],"based":[108],"on":[109,150],"framework":[112],"stacked":[117],"bottleneck":[118],"features.":[119],"These":[120],"features,":[121],"extracted":[122],"from":[123],"second":[125],"level":[126],"DNNs,":[128],"modelled":[130],"by":[131],"classical":[133],"Gaussian":[134],"Mixture":[135],"(GMM)":[137],"ASR":[138],"system.":[139],"an":[144,151],"absolute":[145],"WER":[146],"1.2%":[149],"Arabic":[152],"Broadcast":[153],"news":[154],"task.":[155],"Index":[156],"Terms:":[157],"DNN,":[158],"I-Vector,":[159],"Bottleneck":[160],"Features,":[161]},"counts_by_year":[{"year":2025,"cited_by_count":1},{"year":2024,"cited_by_count":1},{"year":2021,"cited_by_count":2},{"year":2020,"cited_by_count":5},{"year":2018,"cited_by_count":4},{"year":2017,"cited_by_count":1},{"year":2016,"cited_by_count":5},{"year":2015,"cited_by_count":1}],"updated_date":"2026-07-14T23:27:15.235271","created_date":"2025-10-10T00:00:00"}
