{"id":"https://openalex.org/W56593604","doi":"https://doi.org/10.21437/interspeech.2005-115","title":"Automatic data selection for MLP-based feature extraction for ASR","display_name":"Automatic data selection for MLP-based feature extraction for ASR","publication_year":2005,"publication_date":"2005-09-04","ids":{"openalex":"https://openalex.org/W56593604","doi":"https://doi.org/10.21437/interspeech.2005-115","mag":"56593604"},"language":"en","primary_location":{"id":"doi:10.21437/interspeech.2005-115","is_oa":false,"landing_page_url":"https://doi.org/10.21437/interspeech.2005-115","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Interspeech 2005","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/A5090068120","display_name":"Carmen Pel\u00e1ez-Moreno","orcid":"https://orcid.org/0000-0003-1425-6763"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Carmen Pelaez-Moreno","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101999009","display_name":"Qifeng Zhu","orcid":"https://orcid.org/0000-0002-5303-9924"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Qifeng Zhu","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5021511902","display_name":"Barry Y. Chen","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Barry Y. Chen","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5112003894","display_name":"Nelson Morgan","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Nelson Morgan","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":4,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"229","last_page":"232"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12072","display_name":"Machine Learning and Algorithms","score":0.9983999729156494,"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/T12072","display_name":"Machine Learning and Algorithms","score":0.9983999729156494,"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/T11269","display_name":"Algorithms and Data Compression","score":0.9944999814033508,"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/T11447","display_name":"Blind Source Separation Techniques","score":0.9854000210762024,"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/computer-science","display_name":"Computer science","score":0.8466094732284546},{"id":"https://openalex.org/keywords/feature-extraction","display_name":"Feature extraction","score":0.7232718467712402},{"id":"https://openalex.org/keywords/feature-selection","display_name":"Feature selection","score":0.6087219715118408},{"id":"https://openalex.org/keywords/selection","display_name":"Selection (genetic algorithm)","score":0.5327629446983337},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5164475440979004},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.4824526906013489},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.4413931667804718},{"id":"https://openalex.org/keywords/data-extraction","display_name":"Data extraction","score":0.43032175302505493},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.4106415808200836},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.4029924273490906}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8466094732284546},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.7232718467712402},{"id":"https://openalex.org/C148483581","wikidata":"https://www.wikidata.org/wiki/Q446488","display_name":"Feature selection","level":2,"score":0.6087219715118408},{"id":"https://openalex.org/C81917197","wikidata":"https://www.wikidata.org/wiki/Q628760","display_name":"Selection (genetic algorithm)","level":2,"score":0.5327629446983337},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5164475440979004},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.4824526906013489},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.4413931667804718},{"id":"https://openalex.org/C2777466982","wikidata":"https://www.wikidata.org/wiki/Q5227287","display_name":"Data extraction","level":3,"score":0.43032175302505493},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.4106415808200836},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.4029924273490906},{"id":"https://openalex.org/C199539241","wikidata":"https://www.wikidata.org/wiki/Q7748","display_name":"Law","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},{"id":"https://openalex.org/C2779473830","wikidata":"https://www.wikidata.org/wiki/Q1540899","display_name":"MEDLINE","level":2,"score":0.0},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0},{"id":"https://openalex.org/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","level":1,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.21437/interspeech.2005-115","is_oa":false,"landing_page_url":"https://doi.org/10.21437/interspeech.2005-115","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Interspeech 2005","raw_type":"proceedings-article"},{"id":"pmh:oai:CiteSeerX.psu:10.1.1.70.7314","is_oa":false,"landing_page_url":"http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.70.7314","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"http://www.icsi.berkeley.edu/ftp/global/pub/speech/papers/p2039.pdf","raw_type":"text"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":8,"referenced_works":["https://openalex.org/W169882265","https://openalex.org/W197151588","https://openalex.org/W1482797586","https://openalex.org/W1495019370","https://openalex.org/W1706091990","https://openalex.org/W2142694085","https://openalex.org/W2146197305","https://openalex.org/W2155925556"],"related_works":["https://openalex.org/W4205762803","https://openalex.org/W2535856026","https://openalex.org/W2265065644","https://openalex.org/W2134699697","https://openalex.org/W3017188156","https://openalex.org/W2322875716","https://openalex.org/W3147584709","https://openalex.org/W2977677679","https://openalex.org/W4386564352","https://openalex.org/W2952668426"],"abstract_inverted_index":{"The":[0],"use":[1,22,50],"of":[2,12,26,46,51,98],"huge":[3],"databases":[4,54],"in":[5,16,40,88],"ASR":[6,13],"has":[7],"become":[8],"an":[9,24],"important":[10],"source":[11],"system":[14],"improvements":[15],"the":[17,27,33,41,44,57,65,99],"last":[18],"years.":[19],"However,":[20],"their":[21],"demands":[23],"increase":[25],"computational":[28,66],"resources":[29],"necessary":[30],"to":[31,75,84],"train":[32],"recognizers.":[34],"Several":[35],"techniques":[36],"have":[37],"been":[38],"proposed":[39],"literature":[42],"with":[43],"purpose":[45],"making":[47],"a":[48,73,79],"better":[49],"these":[52],"enormous":[53],"by":[55,93],"selecting":[56],"most":[58],"\u2018informative":[59],"\u2018":[60],"portions":[61],"and":[62],"thus":[63],"reducing":[64],"burden.":[67],"In":[68],"this":[69],"paper,":[70],"we":[71],"present":[72],"technique":[74],"select":[76],"samples":[77],"from":[78],"database":[80],"that":[81],"allows":[82],"us":[83],"obtain":[85],"similar":[86],"results":[87],"MLP-based":[89],"feature":[90],"extraction":[91],"stages":[92],"using":[94],"around":[95],"60":[96],"%":[97],"data.":[100],"1.":[101]},"counts_by_year":[{"year":2025,"cited_by_count":1},{"year":2018,"cited_by_count":1}],"updated_date":"2026-07-14T23:27:15.235271","created_date":"2025-10-10T00:00:00"}
