{"id":"https://openalex.org/W4323520209","doi":"https://doi.org/10.1145/3578741.3578779","title":"Context Prefix Tree Beam Search Algorithm Based on Domain Classification","display_name":"Context Prefix Tree Beam Search Algorithm Based on Domain Classification","publication_year":2022,"publication_date":"2022-12-23","ids":{"openalex":"https://openalex.org/W4323520209","doi":"https://doi.org/10.1145/3578741.3578779"},"language":"en","primary_location":{"id":"doi:10.1145/3578741.3578779","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3578741.3578779","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 2022 5th International Conference on Machine Learning and Natural 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/A5010521669","display_name":"Yajie Zheng","orcid":null},"institutions":[{"id":"https://openalex.org/I38877650","display_name":"Zhengzhou University","ror":"https://ror.org/04ypx8c21","country_code":"CN","type":"education","lineage":["https://openalex.org/I38877650"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Yajie Zheng","raw_affiliation_strings":["Zhengzhou University, China"],"affiliations":[{"raw_affiliation_string":"Zhengzhou University, China","institution_ids":["https://openalex.org/I38877650"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101406894","display_name":"Dan Qu","orcid":"https://orcid.org/0000-0002-8876-5117"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Dan Qu","raw_affiliation_strings":["Information Engineering University, China"],"affiliations":[{"raw_affiliation_string":"Information Engineering University, China","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5074428051","display_name":"Xukui Yang","orcid":"https://orcid.org/0000-0002-7989-7089"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Xukui Yang","raw_affiliation_strings":["Information Engineering University, China"],"affiliations":[{"raw_affiliation_string":"Information Engineering University, China","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101560152","display_name":"Yaqi Chen","orcid":"https://orcid.org/0000-0001-6301-802X"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Yaqi Chen","raw_affiliation_strings":["Information Engineering University, China"],"affiliations":[{"raw_affiliation_string":"Information Engineering University, China","institution_ids":[]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5020326079","display_name":"Xiaolin Jiao","orcid":"https://orcid.org/0000-0003-2410-910X"},"institutions":[{"id":"https://openalex.org/I38877650","display_name":"Zhengzhou University","ror":"https://ror.org/04ypx8c21","country_code":"CN","type":"education","lineage":["https://openalex.org/I38877650"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xiaolin Jiao","raw_affiliation_strings":["Zhengzhou University, China"],"affiliations":[{"raw_affiliation_string":"Zhengzhou University, China","institution_ids":["https://openalex.org/I38877650"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":5,"corresponding_author_ids":["https://openalex.org/A5010521669"],"corresponding_institution_ids":["https://openalex.org/I38877650"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.17921665,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"185","last_page":"189"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10201","display_name":"Speech Recognition and Synthesis","score":0.9994999766349792,"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":0.9994999766349792,"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":0.9977999925613403,"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/T10028","display_name":"Topic Modeling","score":0.9922999739646912,"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/beam-search","display_name":"Beam search","score":0.7524144649505615},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7515548467636108},{"id":"https://openalex.org/keywords/prefix","display_name":"Prefix","score":0.6607264876365662},{"id":"https://openalex.org/keywords/context","display_name":"Context (archaeology)","score":0.587203323841095},{"id":"https://openalex.org/keywords/trie","display_name":"Trie","score":0.5672430992126465},{"id":"https://openalex.org/keywords/tree","display_name":"Tree (set theory)","score":0.5611692667007446},{"id":"https://openalex.org/keywords/pruning","display_name":"Pruning","score":0.5410858392715454},{"id":"https://openalex.org/keywords/domain","display_name":"Domain (mathematical analysis)","score":0.5101080536842346},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.4826010465621948},{"id":"https://openalex.org/keywords/matching","display_name":"Matching (statistics)","score":0.4802568256855011},{"id":"https://openalex.org/keywords/set","display_name":"Set (abstract data type)","score":0.4796343445777893},{"id":"https://openalex.org/keywords/word-error-rate","display_name":"Word error rate","score":0.46633219718933105},{"id":"https://openalex.org/keywords/test-set","display_name":"Test set","score":0.4328536093235016},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.39930668473243713},{"id":"https://openalex.org/keywords/speech-recognition","display_name":"Speech recognition","score":0.34592562913894653},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.3316289782524109},{"id":"https://openalex.org/keywords/search-algorithm","display_name":"Search algorithm","score":0.3307996392250061},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.28459039330482483},{"id":"https://openalex.org/keywords/data-structure","display_name":"Data structure","score":0.16542598605155945},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.1558554470539093},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.07031011581420898}],"concepts":[{"id":"https://openalex.org/C19889080","wikidata":"https://www.wikidata.org/wiki/Q2835852","display_name":"Beam search","level":3,"score":0.7524144649505615},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7515548467636108},{"id":"https://openalex.org/C141603448","wikidata":"https://www.wikidata.org/wiki/Q134830","display_name":"Prefix","level":2,"score":0.6607264876365662},{"id":"https://openalex.org/C2779343474","wikidata":"https://www.wikidata.org/wiki/Q3109175","display_name":"Context (archaeology)","level":2,"score":0.587203323841095},{"id":"https://openalex.org/C190290938","wikidata":"https://www.wikidata.org/wiki/Q387015","display_name":"Trie","level":3,"score":0.5672430992126465},{"id":"https://openalex.org/C113174947","wikidata":"https://www.wikidata.org/wiki/Q2859736","display_name":"Tree (set theory)","level":2,"score":0.5611692667007446},{"id":"https://openalex.org/C108010975","wikidata":"https://www.wikidata.org/wiki/Q500094","display_name":"Pruning","level":2,"score":0.5410858392715454},{"id":"https://openalex.org/C36503486","wikidata":"https://www.wikidata.org/wiki/Q11235244","display_name":"Domain (mathematical analysis)","level":2,"score":0.5101080536842346},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4826010465621948},{"id":"https://openalex.org/C165064840","wikidata":"https://www.wikidata.org/wiki/Q1321061","display_name":"Matching (statistics)","level":2,"score":0.4802568256855011},{"id":"https://openalex.org/C177264268","wikidata":"https://www.wikidata.org/wiki/Q1514741","display_name":"Set (abstract data type)","level":2,"score":0.4796343445777893},{"id":"https://openalex.org/C40969351","wikidata":"https://www.wikidata.org/wiki/Q3516228","display_name":"Word error rate","level":2,"score":0.46633219718933105},{"id":"https://openalex.org/C169903167","wikidata":"https://www.wikidata.org/wiki/Q3985153","display_name":"Test set","level":2,"score":0.4328536093235016},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.39930668473243713},{"id":"https://openalex.org/C28490314","wikidata":"https://www.wikidata.org/wiki/Q189436","display_name":"Speech recognition","level":1,"score":0.34592562913894653},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.3316289782524109},{"id":"https://openalex.org/C125583679","wikidata":"https://www.wikidata.org/wiki/Q755673","display_name":"Search algorithm","level":2,"score":0.3307996392250061},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.28459039330482483},{"id":"https://openalex.org/C162319229","wikidata":"https://www.wikidata.org/wiki/Q175263","display_name":"Data structure","level":2,"score":0.16542598605155945},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.1558554470539093},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.07031011581420898},{"id":"https://openalex.org/C151730666","wikidata":"https://www.wikidata.org/wiki/Q7205","display_name":"Paleontology","level":1,"score":0.0},{"id":"https://openalex.org/C134306372","wikidata":"https://www.wikidata.org/wiki/Q7754","display_name":"Mathematical analysis","level":1,"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/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","level":0,"score":0.0},{"id":"https://openalex.org/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"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/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3578741.3578779","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3578741.3578779","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 2022 5th International Conference on Machine Learning and Natural Language Processing","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.6499999761581421,"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":18,"referenced_works":["https://openalex.org/W179875071","https://openalex.org/W1832693441","https://openalex.org/W2327501763","https://openalex.org/W2402268235","https://openalex.org/W2886319145","https://openalex.org/W2889012072","https://openalex.org/W2892009249","https://openalex.org/W2936774411","https://openalex.org/W2937402758","https://openalex.org/W2962824709","https://openalex.org/W2972625221","https://openalex.org/W2973172693","https://openalex.org/W3097239815","https://openalex.org/W3140235797","https://openalex.org/W3161860537","https://openalex.org/W3198004110","https://openalex.org/W3203701724","https://openalex.org/W6739901393"],"related_works":["https://openalex.org/W54192826","https://openalex.org/W2074308207","https://openalex.org/W2395357979","https://openalex.org/W2795037468","https://openalex.org/W1754202134","https://openalex.org/W3092113474","https://openalex.org/W2800763970","https://openalex.org/W4386269615","https://openalex.org/W4390091683","https://openalex.org/W2104971205"],"abstract_inverted_index":{"Nowadays,":[0],"the":[1,60,80,85,88,99,102,126,133,144,154,166,169],"end-to-end":[2],"(E2E)":[3],"speech":[4],"recognition":[5],"model":[6],"has":[7,162],"achieved":[8],"good":[9],"performance,":[10],"but":[11],"it":[12],"performs":[13],"worse":[14],"on":[15,33,165],"utterances":[16],"containing":[17],"infrequent":[18],"proper":[19],"nouns.":[20],"In":[21],"this":[22,123],"work,we":[23],"proposed":[24,96],"a":[25],"context":[26,61,155],"prefix":[27,62],"tree":[28,63],"beam":[29,56,82],"search":[30,48,57],"algorithm":[31],"based":[32],"domain":[34,113,130],"classification":[35,114],"to":[36,40,47,79,97,118,121],"improve":[37],"its":[38],"ability":[39],"recognize":[41],"contextual":[42,67,107,138],"phrases.":[43],"It":[44],"is":[45,95,109,116,149,158],"used":[46,117],"for":[49],"matching":[50,81],"candidate":[51],"characters":[52],"before":[53],"pruning":[54],"in":[55,64],"by":[58,76,151,160],"constructing":[59],"advance.":[65],"The":[66,112],"phrases":[68,108],"can":[69],"be":[70],"preserved":[71],"from":[72],"being":[73],"pruned":[74],"prematurely":[75],"adding":[77],"scores":[78],"path.":[83],"At":[84],"same":[86],"time,":[87],"pre-enhancement":[89],"score":[90],"and":[91,153],"length":[92],"reward":[93],"method":[94,115,124],"address":[98],"problem":[100],"that":[101,143],"biasing":[103],"effect":[104,164],"of":[105,128,168],"short":[106],"not":[110],"obvious.":[111],"decode":[119],"twice":[120],"avoid":[122],"affecting":[125],"performance":[127,167],"general":[129,170],"recognition.":[131],"On":[132],"test":[134],"set":[135],"with":[136],"rich":[137],"phrases,the":[139],"experimental":[140],"results":[141],"demonstrate":[142],"character":[145],"error":[146],"rate":[147,157],"(CER)":[148],"decreased":[150],"1.3%\u20134.8%":[152],"recall":[156],"increased":[159],"6%\u201317%,which":[161],"no":[163],"domain.":[171]},"counts_by_year":[],"updated_date":"2026-03-27T05:58:40.876381","created_date":"2025-10-10T00:00:00"}
