{"id":"https://openalex.org/W2125937262","doi":"https://doi.org/10.1109/iscslp.2010.5684837","title":"A study of large vocabulary speech recognition decoding using finite-state graphs","display_name":"A study of large vocabulary speech recognition decoding using finite-state graphs","publication_year":2010,"publication_date":"2010-11-01","ids":{"openalex":"https://openalex.org/W2125937262","doi":"https://doi.org/10.1109/iscslp.2010.5684837","mag":"2125937262"},"language":"en","primary_location":{"id":"doi:10.1109/iscslp.2010.5684837","is_oa":false,"landing_page_url":"https://doi.org/10.1109/iscslp.2010.5684837","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2010 7th International Symposium on Chinese Spoken Language Processing","raw_type":"proceedings-article"},"type":"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/A5010173604","display_name":"Zhijian Ou","orcid":"https://orcid.org/0000-0002-9018-5074"},"institutions":[{"id":"https://openalex.org/I99065089","display_name":"Tsinghua University","ror":"https://ror.org/03cve4549","country_code":"CN","type":"education","lineage":["https://openalex.org/I99065089"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Zhijian Ou","raw_affiliation_strings":["Department of Electronic Engineering, Tsinghua University, Beijing, China","Department of Electronic Engineering, Tsinghua University, Beijing, CHINA#TAB#"],"affiliations":[{"raw_affiliation_string":"Department of Electronic Engineering, Tsinghua University, Beijing, China","institution_ids":["https://openalex.org/I99065089"]},{"raw_affiliation_string":"Department of Electronic Engineering, Tsinghua University, Beijing, CHINA#TAB#","institution_ids":["https://openalex.org/I99065089"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5102219873","display_name":"Ji Xiao","orcid":null},"institutions":[{"id":"https://openalex.org/I99065089","display_name":"Tsinghua University","ror":"https://ror.org/03cve4549","country_code":"CN","type":"education","lineage":["https://openalex.org/I99065089"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Ji Xiao","raw_affiliation_strings":["Department of Electronic Engineering, Tsinghua University, Beijing, China","Department of Electronic Engineering, Tsinghua University, Beijing, CHINA#TAB#"],"affiliations":[{"raw_affiliation_string":"Department of Electronic Engineering, Tsinghua University, Beijing, China","institution_ids":["https://openalex.org/I99065089"]},{"raw_affiliation_string":"Department of Electronic Engineering, Tsinghua University, Beijing, CHINA#TAB#","institution_ids":["https://openalex.org/I99065089"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5010173604"],"corresponding_institution_ids":["https://openalex.org/I99065089"],"apc_list":null,"apc_paid":null,"fwci":0.451,"has_fulltext":false,"cited_by_count":3,"citation_normalized_percentile":{"value":0.74185541,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":96},"biblio":{"volume":"43","issue":null,"first_page":"123","last_page":"128"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10201","display_name":"Speech Recognition and Synthesis","score":0.9994000196456909,"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":0.9994000196456909,"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/T10181","display_name":"Natural Language Processing Techniques","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/T12031","display_name":"Speech and dialogue systems","score":0.9962000250816345,"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":0.7926315665245056},{"id":"https://openalex.org/keywords/vocabulary","display_name":"Vocabulary","score":0.7664662599563599},{"id":"https://openalex.org/keywords/decoding-methods","display_name":"Decoding methods","score":0.6498245000839233},{"id":"https://openalex.org/keywords/speech-recognition","display_name":"Speech recognition","score":0.6072902083396912},{"id":"https://openalex.org/keywords/viterbi-decoder","display_name":"Viterbi decoder","score":0.5585715770721436},{"id":"https://openalex.org/keywords/viterbi-algorithm","display_name":"Viterbi algorithm","score":0.5310198664665222},{"id":"https://openalex.org/keywords/representation","display_name":"Representation (politics)","score":0.4779393970966339},{"id":"https://openalex.org/keywords/state","display_name":"State (computer science)","score":0.4629747271537781},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.45770004391670227},{"id":"https://openalex.org/keywords/hidden-markov-model","display_name":"Hidden Markov model","score":0.4553154408931732},{"id":"https://openalex.org/keywords/word-error-rate","display_name":"Word error rate","score":0.45378491282463074},{"id":"https://openalex.org/keywords/natural-language-processing","display_name":"Natural language processing","score":0.45106250047683716},{"id":"https://openalex.org/keywords/graph","display_name":"Graph","score":0.41173580288887024},{"id":"https://openalex.org/keywords/theoretical-computer-science","display_name":"Theoretical computer science","score":0.1437532603740692},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.13220372796058655},{"id":"https://openalex.org/keywords/linguistics","display_name":"Linguistics","score":0.06919699907302856}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7926315665245056},{"id":"https://openalex.org/C2777601683","wikidata":"https://www.wikidata.org/wiki/Q6499736","display_name":"Vocabulary","level":2,"score":0.7664662599563599},{"id":"https://openalex.org/C57273362","wikidata":"https://www.wikidata.org/wiki/Q576722","display_name":"Decoding methods","level":2,"score":0.6498245000839233},{"id":"https://openalex.org/C28490314","wikidata":"https://www.wikidata.org/wiki/Q189436","display_name":"Speech recognition","level":1,"score":0.6072902083396912},{"id":"https://openalex.org/C117379686","wikidata":"https://www.wikidata.org/wiki/Q6996459","display_name":"Viterbi decoder","level":3,"score":0.5585715770721436},{"id":"https://openalex.org/C60582962","wikidata":"https://www.wikidata.org/wiki/Q83886","display_name":"Viterbi algorithm","level":3,"score":0.5310198664665222},{"id":"https://openalex.org/C2776359362","wikidata":"https://www.wikidata.org/wiki/Q2145286","display_name":"Representation (politics)","level":3,"score":0.4779393970966339},{"id":"https://openalex.org/C48103436","wikidata":"https://www.wikidata.org/wiki/Q599031","display_name":"State (computer science)","level":2,"score":0.4629747271537781},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.45770004391670227},{"id":"https://openalex.org/C23224414","wikidata":"https://www.wikidata.org/wiki/Q176769","display_name":"Hidden Markov model","level":2,"score":0.4553154408931732},{"id":"https://openalex.org/C40969351","wikidata":"https://www.wikidata.org/wiki/Q3516228","display_name":"Word error rate","level":2,"score":0.45378491282463074},{"id":"https://openalex.org/C204321447","wikidata":"https://www.wikidata.org/wiki/Q30642","display_name":"Natural language processing","level":1,"score":0.45106250047683716},{"id":"https://openalex.org/C132525143","wikidata":"https://www.wikidata.org/wiki/Q141488","display_name":"Graph","level":2,"score":0.41173580288887024},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.1437532603740692},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.13220372796058655},{"id":"https://openalex.org/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","level":1,"score":0.06919699907302856},{"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/C94625758","wikidata":"https://www.wikidata.org/wiki/Q7163","display_name":"Politics","level":2,"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/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/iscslp.2010.5684837","is_oa":false,"landing_page_url":"https://doi.org/10.1109/iscslp.2010.5684837","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2010 7th International Symposium on Chinese Spoken Language Processing","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/4","display_name":"Quality Education","score":0.5600000023841858}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":21,"referenced_works":["https://openalex.org/W12115718","https://openalex.org/W27187656","https://openalex.org/W34000504","https://openalex.org/W99223150","https://openalex.org/W153444084","https://openalex.org/W1493254853","https://openalex.org/W1534536260","https://openalex.org/W1895481600","https://openalex.org/W1967325250","https://openalex.org/W2097003869","https://openalex.org/W2125838338","https://openalex.org/W2157953146","https://openalex.org/W2380696899","https://openalex.org/W4285719527","https://openalex.org/W6600511685","https://openalex.org/W6601066586","https://openalex.org/W6601391525","https://openalex.org/W6604039549","https://openalex.org/W6606255316","https://openalex.org/W6631925876","https://openalex.org/W6674447887"],"related_works":["https://openalex.org/W2136652457","https://openalex.org/W2169849734","https://openalex.org/W2160171981","https://openalex.org/W2102309991","https://openalex.org/W2116722627","https://openalex.org/W2385954530","https://openalex.org/W1975869217","https://openalex.org/W2236912844","https://openalex.org/W1795315578","https://openalex.org/W2373954783"],"abstract_inverted_index":{"The":[0,56,74,122],"use":[1,44],"of":[2,109],"weighted":[3],"finite-state":[4,71],"transducers":[5],"(WFSTs)":[6],"has":[7],"become":[8],"an":[9],"attractive":[10],"technique":[11],"for":[12,83,144,151],"building":[13],"large":[14],"vocabulary":[15],"continuous":[16],"speech":[17,84,101],"recognition":[18,85,102,154],"decoders.":[19],"Conventionally,":[20],"the":[21,45,53,130],"compiled":[22,57],"search":[23,54],"network":[24],"is":[25,32,59,77,111,136],"represented":[26],"as":[27],"a":[28,37,64,98,152],"standard":[29,46],"WFST,":[30],"which":[31,68,104,128],"then":[33,60],"directly":[34],"fed":[35],"into":[36],"Viterbi":[38,81],"decoder.":[39],"In":[40],"this":[41],"work,":[42],"we":[43,69,105],"WFST":[47,58],"representations":[48],"and":[49,86,120,141],"operations":[50],"during":[51],"compiling":[52],"network.":[55],"equivalently":[61],"converted":[62],"to":[63,80,96,138],"new":[65,131],"graphical":[66],"representation,":[67],"call":[70,106],"graph":[72],"(FSG).":[73],"resulting":[75],"FSG":[76,132],"more":[78,87],"tailored":[79],"decoding":[82],"compact":[88],"in":[89,134],"memory.":[90],"This":[91],"paper":[92],"presents":[93],"our":[94],"effort":[95],"build":[97],"state-of-the-art":[99],"WFST-based":[100],"system,":[103],"GrpDecoder.":[107],"Benchmarking":[108],"GrpDecoder":[110,127],"carried":[112],"out":[113],"separately":[114],"on":[115],"two":[116],"languages":[117],"-":[118],"English":[119],"Mandarin.":[121],"test":[123],"results":[124],"show":[125],"that":[126],"uses":[129],"representation":[133],"searching":[135],"superior":[137],"HTK's":[139],"HDecode":[140],"IDIAP's":[142],"Juicer":[143],"both":[145],"languages,":[146],"achieving":[147],"lower":[148],"error":[149],"rates":[150],"given":[153],"speed.":[155]},"counts_by_year":[{"year":2024,"cited_by_count":2},{"year":2012,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}