{"id":"https://openalex.org/W2188969719","doi":"https://doi.org/10.21437/interspeech.2011-360","title":"Response probability based decoding algorithm for large vocabulary continuous speech recognition","display_name":"Response probability based decoding algorithm for large vocabulary continuous speech recognition","publication_year":2011,"publication_date":"2011-08-27","ids":{"openalex":"https://openalex.org/W2188969719","doi":"https://doi.org/10.21437/interspeech.2011-360","mag":"2188969719"},"language":"en","primary_location":{"id":"doi:10.21437/interspeech.2011-360","is_oa":false,"landing_page_url":"https://doi.org/10.21437/interspeech.2011-360","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Interspeech 2011","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/A5084649692","display_name":"Zhanlei Yang","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Zhanlei Yang","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5021932420","display_name":"Chao Hao","orcid":"https://orcid.org/0000-0001-6700-9446"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Hao Chao","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5039635290","display_name":"Wenju Liu","orcid":"https://orcid.org/0000-0001-9088-8282"},"institutions":[{"id":"https://openalex.org/I19820366","display_name":"Chinese Academy of Sciences","ror":"https://ror.org/034t30j35","country_code":"CN","type":"government","lineage":["https://openalex.org/I19820366"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Wenju Liu","raw_affiliation_strings":["Institute of Automation. Chinese Academy of Sciences"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Institute of Automation. Chinese Academy of Sciences","institution_ids":["https://openalex.org/I19820366"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.2698,"has_fulltext":false,"cited_by_count":1,"citation_normalized_percentile":{"value":0.55037829,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":94},"biblio":{"volume":null,"issue":null,"first_page":"1929","last_page":"1932"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10201","display_name":"Speech Recognition and Synthesis","score":0.9993000030517578,"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":0.9993000030517578,"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":0.9914000034332275,"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":0.9634000062942505,"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/decoding-methods","display_name":"Decoding methods","score":0.7560268640518188},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7449559569358826},{"id":"https://openalex.org/keywords/language-model","display_name":"Language model","score":0.7138738036155701},{"id":"https://openalex.org/keywords/speech-recognition","display_name":"Speech recognition","score":0.690782368183136},{"id":"https://openalex.org/keywords/pruning","display_name":"Pruning","score":0.5183273553848267},{"id":"https://openalex.org/keywords/word-error-rate","display_name":"Word error rate","score":0.5131464600563049},{"id":"https://openalex.org/keywords/vocabulary","display_name":"Vocabulary","score":0.5074612498283386},{"id":"https://openalex.org/keywords/mandarin-chinese","display_name":"Mandarin Chinese","score":0.48626649379730225},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.4707411229610443},{"id":"https://openalex.org/keywords/speech-coding","display_name":"Speech coding","score":0.4445716142654419},{"id":"https://openalex.org/keywords/acoustic-model","display_name":"Acoustic model","score":0.43895477056503296},{"id":"https://openalex.org/keywords/gaussian","display_name":"Gaussian","score":0.43516743183135986},{"id":"https://openalex.org/keywords/acoustic-space","display_name":"Acoustic space","score":0.42078182101249695},{"id":"https://openalex.org/keywords/hidden-markov-model","display_name":"Hidden Markov model","score":0.4187672436237335},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.4055618643760681},{"id":"https://openalex.org/keywords/speech-processing","display_name":"Speech processing","score":0.3291352093219757}],"concepts":[{"id":"https://openalex.org/C57273362","wikidata":"https://www.wikidata.org/wiki/Q576722","display_name":"Decoding methods","level":2,"score":0.7560268640518188},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7449559569358826},{"id":"https://openalex.org/C137293760","wikidata":"https://www.wikidata.org/wiki/Q3621696","display_name":"Language model","level":2,"score":0.7138738036155701},{"id":"https://openalex.org/C28490314","wikidata":"https://www.wikidata.org/wiki/Q189436","display_name":"Speech recognition","level":1,"score":0.690782368183136},{"id":"https://openalex.org/C108010975","wikidata":"https://www.wikidata.org/wiki/Q500094","display_name":"Pruning","level":2,"score":0.5183273553848267},{"id":"https://openalex.org/C40969351","wikidata":"https://www.wikidata.org/wiki/Q3516228","display_name":"Word error rate","level":2,"score":0.5131464600563049},{"id":"https://openalex.org/C2777601683","wikidata":"https://www.wikidata.org/wiki/Q6499736","display_name":"Vocabulary","level":2,"score":0.5074612498283386},{"id":"https://openalex.org/C138954614","wikidata":"https://www.wikidata.org/wiki/Q9192","display_name":"Mandarin Chinese","level":2,"score":0.48626649379730225},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.4707411229610443},{"id":"https://openalex.org/C13895895","wikidata":"https://www.wikidata.org/wiki/Q3270773","display_name":"Speech coding","level":2,"score":0.4445716142654419},{"id":"https://openalex.org/C155635449","wikidata":"https://www.wikidata.org/wiki/Q4674699","display_name":"Acoustic model","level":3,"score":0.43895477056503296},{"id":"https://openalex.org/C163716315","wikidata":"https://www.wikidata.org/wiki/Q901177","display_name":"Gaussian","level":2,"score":0.43516743183135986},{"id":"https://openalex.org/C108250783","wikidata":"https://www.wikidata.org/wiki/Q4674710","display_name":"Acoustic space","level":3,"score":0.42078182101249695},{"id":"https://openalex.org/C23224414","wikidata":"https://www.wikidata.org/wiki/Q176769","display_name":"Hidden Markov model","level":2,"score":0.4187672436237335},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4055618643760681},{"id":"https://openalex.org/C61328038","wikidata":"https://www.wikidata.org/wiki/Q3358061","display_name":"Speech processing","level":2,"score":0.3291352093219757},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0},{"id":"https://openalex.org/C204723758","wikidata":"https://www.wikidata.org/wiki/Q3882459","display_name":"Acoustic wave","level":2,"score":0.0},{"id":"https://openalex.org/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","level":1,"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/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","level":0,"score":0.0},{"id":"https://openalex.org/C6557445","wikidata":"https://www.wikidata.org/wiki/Q173113","display_name":"Agronomy","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/C62520636","wikidata":"https://www.wikidata.org/wiki/Q944","display_name":"Quantum mechanics","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.21437/interspeech.2011-360","is_oa":false,"landing_page_url":"https://doi.org/10.21437/interspeech.2011-360","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Interspeech 2011","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.699999988079071,"id":"https://metadata.un.org/sdg/4","display_name":"Quality Education"}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":12,"referenced_works":["https://openalex.org/W1825623823","https://openalex.org/W1967325250","https://openalex.org/W1977434607","https://openalex.org/W2008554732","https://openalex.org/W2034537249","https://openalex.org/W2043422002","https://openalex.org/W2043547528","https://openalex.org/W2134659216","https://openalex.org/W2149298150","https://openalex.org/W2151058131","https://openalex.org/W2161347627","https://openalex.org/W3031363333"],"related_works":["https://openalex.org/W2163874654","https://openalex.org/W70208120","https://openalex.org/W1911859126","https://openalex.org/W3081187864","https://openalex.org/W2057566829","https://openalex.org/W4380605396","https://openalex.org/W2803306015","https://openalex.org/W3133352777","https://openalex.org/W2008737763","https://openalex.org/W151018310"],"abstract_inverted_index":{"Acoustic":[0],"space":[1],"is":[2,63,79,108,116,126],"made":[3],"up":[4],"of":[5,29,49],"phonemes,":[6],"and":[7,25,70,89,118],"it":[8],"can":[9],"be":[10],"modeled":[11],"using":[12],"universal":[13],"background":[14],"model":[15,62,68,72,115,125],"(UBM).":[16],"Therefore,":[17],"there":[18],"are":[19],"some":[20],"relations":[21,36],"between":[22],"the":[23,30,46,53,77,93],"phonemes":[24],"Gaussian":[26],"mixture":[27],"components":[28],"UBM.":[31],"This":[32],"paper":[33],"represents":[34],"these":[35],"by":[37,111,119],"proposing":[38],"a":[39],"response":[40,135],"probability":[41,136],"(RP)":[42],"model,":[43],"which":[44],"describes":[45],"location":[47],"information":[48],"speech":[50,102,130],"observations":[51],"within":[52],"whole":[54],"acoustic":[55,67],"space.":[56],"At":[57],"decoding":[58,132],"stage,":[59],"proposed":[60],"RP":[61,114,124],"fused":[64],"with":[65],"traditional":[66],"(AM)":[69],"language":[71],"(LM).":[73],"After":[74],"integrating":[75],"RP,":[76],"decoder":[78],"guided":[80],"to":[81,91],"weaken":[82],"or":[83],"enhance":[84],"different":[85],"path":[86],"candidates":[87],"respectively":[88],"directed":[90],"extend":[92],"most":[94],"promising":[95],"paths.":[96],"Experiments":[97],"conducted":[98],"on":[99],"Mandarin":[100],"broadcasting":[101],"show":[103],"that":[104],"character":[105],"error":[106],"rate":[107],"relatively":[109],"reduced":[110],"9.15%":[112],"when":[113,121],"used":[117],"11.89%":[120],"an":[122],"improved":[123],"used.":[127],"Index":[128],"Terms:":[129],"recognition,":[131],"algorithm,":[133],"pruning,":[134]},"counts_by_year":[{"year":2012,"cited_by_count":1}],"updated_date":"2026-07-29T14:22:42.915294","created_date":"2025-10-10T00:00:00"}
