乐胖代购免代理版

{"id":"https://openalex.org/W2106700313","doi":"https://doi.org/10.1109/icassp.2012.6289023","title":"Model-based noise reduction leveraging frequency-wise confidence metric for in-car speech recognition","display_name":"Model-based noise reduction leveraging frequency-wise confidence metric for in-car speech recognition","publication_year":2012,"publication_date":"2012-03-01","ids":{"openalex":"https://openalex.org/W2106700313","doi":"https://doi.org/10.1109/icassp.2012.6289023","mag":"2106700313"},"language":"en","primary_location":{"is_oa":false,"landing_page_url":"https://doi.org/10.1109/icassp.2012.6289023","pdf_url":null,"source":null,"license":null,"license_id":null,"version":null,"is_accepted":false,"is_published":false},"type":"article","type_crossref":"proceedings-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/A5033500018","display_name":"Osamu Ichikawa","orcid":null},"institutions":[{"id":"https://openalex.org/I1341412227","display_name":"IBM (United States)","ror":"https://ror.org/05hh8d621","country_code":"US","type":"funder","lineage":["https://openalex.org/I1341412227"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Osamu Ichikawa","raw_affiliation_strings":["IBM Research - Tokyo, Yamato, 242-8502, JAPAN"],"affiliations":[{"raw_affiliation_string":"IBM Research - Tokyo, Yamato, 242-8502, JAPAN","institution_ids":["https://openalex.org/I1341412227"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5088753951","display_name":"Steven J. Rennie","orcid":null},"institutions":[{"id":"https://openalex.org/I1341412227","display_name":"IBM (United States)","ror":"https://ror.org/05hh8d621","country_code":"US","type":"funder","lineage":["https://openalex.org/I1341412227"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Steven J. Rennie","raw_affiliation_strings":["[IBM T.J. Watson Research Center, Yorktown Heights, NY 10598, USA]"],"affiliations":[{"raw_affiliation_string":"[IBM T.J. Watson Research Center, Yorktown Heights, NY 10598, USA]","institution_ids":["https://openalex.org/I1341412227"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5037089480","display_name":"Takashi Fukuda","orcid":"https://orcid.org/0000-0001-9599-6274"},"institutions":[{"id":"https://openalex.org/I1341412227","display_name":"IBM (United States)","ror":"https://ror.org/05hh8d621","country_code":"US","type":"funder","lineage":["https://openalex.org/I1341412227"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Takashi Fukuda","raw_affiliation_strings":["IBM Research - Tokyo, Yamato, 242-8502, JAPAN"],"affiliations":[{"raw_affiliation_string":"IBM Research - Tokyo, Yamato, 242-8502, JAPAN","institution_ids":["https://openalex.org/I1341412227"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5083574298","display_name":"Masafumi Nishimura","orcid":"https://orcid.org/0000-0001-7633-9340"},"institutions":[{"id":"https://openalex.org/I1341412227","display_name":"IBM (United States)","ror":"https://ror.org/05hh8d621","country_code":"US","type":"funder","lineage":["https://openalex.org/I1341412227"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Masafumi Nishimura","raw_affiliation_strings":["IBM Research - Tokyo, Yamato, 242-8502, JAPAN"],"affiliations":[{"raw_affiliation_string":"IBM Research - Tokyo, Yamato, 242-8502, JAPAN","institution_ids":["https://openalex.org/I1341412227"]}]}],"institution_assertions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":true,"fulltext_origin":"ngrams","cited_by_count":4,"citation_normalized_percentile":{"value":0.484883,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":78,"max":80},"biblio":{"volume":null,"issue":null,"first_page":"4921","last_page":"4924"},"is_retracted":false,"is_paratext":false,"primary_topic":{"id":"https://openalex.org/T10860","display_name":"Speech and Audio Processing","score":0.9999,"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":0.9999,"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/T10201","display_name":"Speech Recognition and Synthesis","score":0.9997,"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/T11309","display_name":"Music and Audio Processing","score":0.9989,"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/word-error-rate","display_name":"Word error rate","score":0.5554915}],"concepts":[{"id":"https://openalex.org/C28490314","wikidata":"https://www.wikidata.org/wiki/Q189436","display_name":"Speech recognition","level":1,"score":0.6954271},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6466629},{"id":"https://openalex.org/C40969351","wikidata":"https://www.wikidata.org/wiki/Q3516228","display_name":"Word error rate","level":2,"score":0.5554915},{"id":"https://openalex.org/C163294075","wikidata":"https://www.wikidata.org/wiki/Q581861","display_name":"Noise reduction","level":2,"score":0.5500766},{"id":"https://openalex.org/C2776182073","wikidata":"https://www.wikidata.org/wiki/Q7575395","display_name":"Speech enhancement","level":3,"score":0.4844875},{"id":"https://openalex.org/C176217482","wikidata":"https://www.wikidata.org/wiki/Q860554","display_name":"Metric (unit)","level":2,"score":0.4797498},{"id":"https://openalex.org/C19118579","wikidata":"https://www.wikidata.org/wiki/Q786423","display_name":"Frequency domain","level":2,"score":0.46984476},{"id":"https://openalex.org/C99498987","wikidata":"https://www.wikidata.org/wiki/Q2210247","display_name":"Noise (video)","level":3,"score":0.4660543},{"id":"https://openalex.org/C49937458","wikidata":"https://www.wikidata.org/wiki/Q2599292","display_name":"Probabilistic logic","level":2,"score":0.44092953},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.43356383},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.3761808},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.101641685},{"id":"https://openalex.org/C21547014","wikidata":"https://www.wikidata.org/wiki/Q1423657","display_name":"Operations management","level":1,"score":0.0},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.0},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"is_oa":false,"landing_page_url":"https://doi.org/10.1109/icassp.2012.6289023","pdf_url":null,"source":null,"license":null,"license_id":null,"version":null,"is_accepted":false,"is_published":false}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.79,"display_name":"Peace, justice, and strong institutions","id":"https://metadata.un.org/sdg/16"}],"grants":[],"datasets":[],"versions":[],"referenced_works_count":9,"referenced_works":["https://openalex.org/W1279245896","https://openalex.org/W2016077841","https://openalex.org/W2031274324","https://openalex.org/W2103202874","https://openalex.org/W2124611315","https://openalex.org/W2126597753","https://openalex.org/W2147245568","https://openalex.org/W2149457403","https://openalex.org/W35070573"],"related_works":["https://openalex.org/W4214692512","https://openalex.org/W3168109306","https://openalex.org/W2962707588","https://openalex.org/W2959160600","https://openalex.org/W2516933085","https://openalex.org/W2401089611","https://openalex.org/W2387796150","https://openalex.org/W2373767407","https://openalex.org/W2358461432","https://openalex.org/W1630865680"],"abstract_inverted_index":{"Model-based":[0],"approaches":[1],"for":[2,27,91],"noise":[3],"reduction":[4],"effectively":[5],"improve":[6],"the":[7,20,42,59,78,88,92,104,136],"performance":[8],"of":[9,17,62,94,106,131],"automatic":[10],"speech":[11,29,64,95],"recognition":[12],"in":[13,41,77],"noisy":[14],"environments.":[15],"Most":[16],"them":[18],"use":[19,82],"Minimum":[21],"Mean":[22],"Square":[23],"Estimate":[24],"(MMSE)":[25],"criterion":[26],"de-noised":[28],"estimates.":[30],"In":[31],"general,":[32],"an":[33,119,141],"observation":[34],"has":[35],"speech-dominant":[36],"bands":[37,40,56,68],"and":[38],"noise-dominant":[39],"Mel":[43,79],"spectral":[44],"domain.":[45],"This":[46,97],"paper":[47],"introduces":[48],"a":[49],"method":[50,124,139],"to":[51,54,102,111,133],"add":[52],"weight":[53],"speech-dominated":[55],"when":[57],"evaluating":[58],"posterior":[60],"probability":[61],"each":[63,112],"state,":[65],"as":[66,87],"these":[67],"are":[69],"generally":[70],"more":[71],"reliable.":[72],"To":[73],"leverage":[74],"high-resolution":[75],"information":[76,98],"domain,":[80],"we":[81],"Local":[83],"Peak":[84],"Weight":[85],"(LPW)":[86],"confidence":[89],"metric":[90],"degree":[93],"dominance.":[96],"is":[99,109],"also":[100],"used":[101],"regulate":[103],"amount":[105],"compensation":[107],"that":[108],"applied":[110],"frequency":[113],"band":[114],"during":[115],"feature":[116],"reconstruction":[117],"under":[118],"integrated":[120],"probabilistic":[121],"model.":[122],"The":[123],"produced":[125],"relative":[126],"word":[127,143],"error":[128],"rate":[129],"improvements":[130],"up":[132],"33.8%":[134],"over":[135],"baseline":[137],"MMSE":[138],"on":[140],"isolated":[142],"task":[144],"with":[145],"car":[146],"noise.":[147]},"abstract_inverted_index_v3":null,"cited_by_api_url":"https://api.openalex.org/works?filter=cites:W2106700313","counts_by_year":[{"year":2023,"cited_by_count":2},{"year":2017,"cited_by_count":1},{"year":2016,"cited_by_count":1}],"updated_date":"2025-04-17T07:52:50.818332","created_date":"2016-06-24"}