{"id":"https://openalex.org/W1769241860","doi":"https://doi.org/10.1109/nnsp.2002.1030073","title":"Linear input network for neural network automata model adaptation","display_name":"Linear input network for neural network automata model adaptation","publication_year":2003,"publication_date":"2003-06-25","ids":{"openalex":"https://openalex.org/W1769241860","doi":"https://doi.org/10.1109/nnsp.2002.1030073","mag":"1769241860"},"language":"en","primary_location":{"id":"doi:10.1109/nnsp.2002.1030073","is_oa":false,"landing_page_url":"https://doi.org/10.1109/nnsp.2002.1030073","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 12th IEEE Workshop on Neural Networks for Signal Processing","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/A5048085326","display_name":"Franco Mana","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"F. Mana","raw_affiliation_strings":["Via Nole, Loquendo S. p. A., Torino, Italy","Loquendo S.p.A, Torino, Italy"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Via Nole, Loquendo S. p. A., Torino, Italy","institution_ids":[]},{"raw_affiliation_string":"Loquendo S.p.A, Torino, Italy","institution_ids":[]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5056510268","display_name":"Roberto Gemello","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"R. Gemello","raw_affiliation_strings":["Via Nole, Loquendo S. p. A., Torino, Italy","Loquendo S.p.A, Torino, Italy"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Via Nole, Loquendo S. p. A., Torino, Italy","institution_ids":[]},{"raw_affiliation_string":"Loquendo S.p.A, Torino, Italy","institution_ids":[]}]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":0,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.1055339,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"3","issue":null,"first_page":"617","last_page":"626"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10860","display_name":"Speech and Audio Processing","score":0.9994000196456909,"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"}},"topics":[{"id":"https://openalex.org/T10860","display_name":"Speech and Audio Processing","score":0.9994000196456909,"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/T11447","display_name":"Blind Source Separation Techniques","score":0.9987000226974487,"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/T10320","display_name":"Neural Networks and Applications","score":0.9984999895095825,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7614413499832153},{"id":"https://openalex.org/keywords/noise-reduction","display_name":"Noise reduction","score":0.6297363638877869},{"id":"https://openalex.org/keywords/microphone","display_name":"Microphone","score":0.5999345183372498},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.5832033157348633},{"id":"https://openalex.org/keywords/noise","display_name":"Noise (video)","score":0.5522027611732483},{"id":"https://openalex.org/keywords/speech-recognition","display_name":"Speech recognition","score":0.5195896625518799},{"id":"https://openalex.org/keywords/reduction","display_name":"Reduction (mathematics)","score":0.44552695751190186},{"id":"https://openalex.org/keywords/gsm","display_name":"GSM","score":0.4246659576892853},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.3232194781303406},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.20722618699073792},{"id":"https://openalex.org/keywords/telecommunications","display_name":"Telecommunications","score":0.16833466291427612},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.09631961584091187}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7614413499832153},{"id":"https://openalex.org/C163294075","wikidata":"https://www.wikidata.org/wiki/Q581861","display_name":"Noise reduction","level":2,"score":0.6297363638877869},{"id":"https://openalex.org/C2778263558","wikidata":"https://www.wikidata.org/wiki/Q46384","display_name":"Microphone","level":3,"score":0.5999345183372498},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.5832033157348633},{"id":"https://openalex.org/C99498987","wikidata":"https://www.wikidata.org/wiki/Q2210247","display_name":"Noise (video)","level":3,"score":0.5522027611732483},{"id":"https://openalex.org/C28490314","wikidata":"https://www.wikidata.org/wiki/Q189436","display_name":"Speech recognition","level":1,"score":0.5195896625518799},{"id":"https://openalex.org/C111335779","wikidata":"https://www.wikidata.org/wiki/Q3454686","display_name":"Reduction (mathematics)","level":2,"score":0.44552695751190186},{"id":"https://openalex.org/C59201141","wikidata":"https://www.wikidata.org/wiki/Q46904","display_name":"GSM","level":2,"score":0.4246659576892853},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.3232194781303406},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.20722618699073792},{"id":"https://openalex.org/C76155785","wikidata":"https://www.wikidata.org/wiki/Q418","display_name":"Telecommunications","level":1,"score":0.16833466291427612},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.09631961584091187},{"id":"https://openalex.org/C68115822","wikidata":"https://www.wikidata.org/wiki/Q1068172","display_name":"Sound pressure","level":2,"score":0.0},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.0},{"id":"https://openalex.org/C2524010","wikidata":"https://www.wikidata.org/wiki/Q8087","display_name":"Geometry","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/nnsp.2002.1030073","is_oa":false,"landing_page_url":"https://doi.org/10.1109/nnsp.2002.1030073","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 12th IEEE Workshop on Neural Networks for Signal Processing","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":14,"referenced_works":["https://openalex.org/W71891565","https://openalex.org/W1553004968","https://openalex.org/W1872566306","https://openalex.org/W2110871230","https://openalex.org/W2122076406","https://openalex.org/W2134167844","https://openalex.org/W2151231072","https://openalex.org/W2153242462","https://openalex.org/W2155196177","https://openalex.org/W2160141226","https://openalex.org/W2164010719","https://openalex.org/W4244452821","https://openalex.org/W6602937256","https://openalex.org/W6632891567"],"related_works":["https://openalex.org/W1823457431","https://openalex.org/W2553656238","https://openalex.org/W4238732447","https://openalex.org/W2155503889","https://openalex.org/W2357191878","https://openalex.org/W4243960761","https://openalex.org/W1997078944","https://openalex.org/W2116284816","https://openalex.org/W2360333859","https://openalex.org/W1968065688"],"abstract_inverted_index":{"The":[0,36,53,95,137,153,181],"paper":[1],"describes":[2],"an":[3,22,40,88],"experimental":[4],"investigation":[5],"of":[6,9,24,63,74,82,131,159,189,207],"the":[7,25,56,69,83,98,110,114,129,157,167,194],"applicability":[8],"linear":[10],"input":[11],"networks":[12],"(LIN)":[13],"as":[14],"a":[15,33,49,64,75,105,171,175,208],"channel":[16,162],"and":[17,71,85,91,163,201,210],"noise":[18,93,150,164,211],"adaptation":[19],"technique":[20,112],"for":[21,161],"application":[23,38,187],"Loquendo":[26],"neural":[27,116],"network":[28,117],"based":[29,148],"speech":[30,118],"recognizer":[31,119],"in":[32,68,80,184],"car":[34,70],"environment.":[35,123],"considered":[37],"is":[39,59,78,101,140,179],"automated":[41],"call":[42,57,99],"center":[43,58,100],"that":[44],"provides":[45],"traffic":[46],"information":[47],"through":[48,104],"voice":[50],"dialogue":[51],"system.":[52],"connection":[54,96],"to":[55,120,127],"achieved":[60,203],"by":[61,197,204],"means":[62],"commercial":[65],"device":[66],"placed":[67,79],"made":[72],"up":[73,103],"microphone":[76],"which":[77],"front":[81],"driver":[84],"equipped":[86],"with":[87,97,143],"echo":[89],"canceller":[90],"built-in":[92],"reduction.":[94],"set":[102],"GSM":[106],"link.":[107],"By":[108],"experiment,":[109],"LIN":[111,138,160,209],"adapts":[113],"basic":[115],"this":[121],"new":[122],"Some":[124],"variants":[125,169],"devoted":[126],"reducing":[128],"number":[130],"estimated":[132],"parameters":[133],"are":[134,170],"also":[135,141],"introduced.":[136],"technique,":[139],"compared":[142],"some":[144],"classical":[145],"denoising":[146],"techniques":[147],"on":[149],"spectral":[151,212],"subtraction.":[152,213],"obtained":[154,196],"results":[155],"confirm":[156],"validity":[158],"adaptation,":[165],"while":[166],"introduced":[168],"valid":[172],"alternative":[173],"when":[174],"reduced":[176],"model":[177],"size":[178],"important.":[180],"best":[182],"performances":[183],"our":[185],"specific":[186],"were":[188,202],"57.14%":[190],"error":[191],"reduction":[192],"versus":[193],"performance":[195],"general":[198],"acoustic":[199],"models":[200],"joint":[205],"use":[206]},"counts_by_year":[],"updated_date":"2026-07-29T14:22:42.915294","created_date":"2025-10-10T00:00:00"}