{"id":"https://openalex.org/W3163135964","doi":"https://doi.org/10.1109/icassp39728.2021.9414158","title":"Code-Switch Speech Rescoring with Monolingual Data","display_name":"Code-Switch Speech Rescoring with Monolingual Data","publication_year":2021,"publication_date":"2021-05-13","ids":{"openalex":"https://openalex.org/W3163135964","doi":"https://doi.org/10.1109/icassp39728.2021.9414158","mag":"3163135964"},"language":"en","primary_location":{"id":"doi:10.1109/icassp39728.2021.9414158","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icassp39728.2021.9414158","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"ICASSP 2021 - 2021 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)","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/A5039857323","display_name":"Guoyu Liu","orcid":"https://orcid.org/0009-0006-3548-7834"},"institutions":[{"id":"https://openalex.org/I2250653659","display_name":"Tencent (China)","ror":"https://ror.org/00hhjss72","country_code":"CN","type":"company","lineage":["https://openalex.org/I2250653659"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Guoyu Liu","raw_affiliation_strings":["Tencent AI Lab"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Tencent AI Lab","institution_ids":["https://openalex.org/I2250653659"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5042872210","display_name":"Lixin Cao","orcid":null},"institutions":[{"id":"https://openalex.org/I2250653659","display_name":"Tencent (China)","ror":"https://ror.org/00hhjss72","country_code":"CN","type":"company","lineage":["https://openalex.org/I2250653659"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Lixin Cao","raw_affiliation_strings":["Tencent AI Lab"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Tencent AI Lab","institution_ids":["https://openalex.org/I2250653659"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I2250653659"],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":7,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"6229","last_page":"6233"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10201","display_name":"Speech Recognition and Synthesis","score":0.9995999932289124,"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":0.9995999932289124,"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":0.9991999864578247,"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":0.994700014591217,"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":0.8790994882583618},{"id":"https://openalex.org/keywords/sentence","display_name":"Sentence","score":0.6754195094108582},{"id":"https://openalex.org/keywords/speech-recognition","display_name":"Speech recognition","score":0.6207022070884705},{"id":"https://openalex.org/keywords/natural-language-processing","display_name":"Natural language processing","score":0.6154776811599731},{"id":"https://openalex.org/keywords/word","display_name":"Word (group theory)","score":0.6025641560554504},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5509575009346008},{"id":"https://openalex.org/keywords/code","display_name":"Code (set theory)","score":0.5408679842948914},{"id":"https://openalex.org/keywords/focus","display_name":"Focus (optics)","score":0.5171005725860596},{"id":"https://openalex.org/keywords/code-switching","display_name":"Code-switching","score":0.50491863489151},{"id":"https://openalex.org/keywords/language-model","display_name":"Language model","score":0.47272437810897827},{"id":"https://openalex.org/keywords/cache-language-model","display_name":"Cache language model","score":0.4292064607143402},{"id":"https://openalex.org/keywords/process","display_name":"Process (computing)","score":0.42123907804489136},{"id":"https://openalex.org/keywords/set","display_name":"Set (abstract data type)","score":0.3899019956588745},{"id":"https://openalex.org/keywords/natural-language","display_name":"Natural language","score":0.1896166205406189},{"id":"https://openalex.org/keywords/linguistics","display_name":"Linguistics","score":0.11808302998542786},{"id":"https://openalex.org/keywords/programming-language","display_name":"Programming language","score":0.11298114061355591},{"id":"https://openalex.org/keywords/universal-networking-language","display_name":"Universal Networking Language","score":0.07738485932350159}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8790994882583618},{"id":"https://openalex.org/C2777530160","wikidata":"https://www.wikidata.org/wiki/Q41796","display_name":"Sentence","level":2,"score":0.6754195094108582},{"id":"https://openalex.org/C28490314","wikidata":"https://www.wikidata.org/wiki/Q189436","display_name":"Speech recognition","level":1,"score":0.6207022070884705},{"id":"https://openalex.org/C204321447","wikidata":"https://www.wikidata.org/wiki/Q30642","display_name":"Natural language processing","level":1,"score":0.6154776811599731},{"id":"https://openalex.org/C90805587","wikidata":"https://www.wikidata.org/wiki/Q10944557","display_name":"Word (group theory)","level":2,"score":0.6025641560554504},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5509575009346008},{"id":"https://openalex.org/C2776760102","wikidata":"https://www.wikidata.org/wiki/Q5139990","display_name":"Code (set theory)","level":3,"score":0.5408679842948914},{"id":"https://openalex.org/C192209626","wikidata":"https://www.wikidata.org/wiki/Q190909","display_name":"Focus (optics)","level":2,"score":0.5171005725860596},{"id":"https://openalex.org/C18552078","wikidata":"https://www.wikidata.org/wiki/Q255615","display_name":"Code-switching","level":2,"score":0.50491863489151},{"id":"https://openalex.org/C137293760","wikidata":"https://www.wikidata.org/wiki/Q3621696","display_name":"Language model","level":2,"score":0.47272437810897827},{"id":"https://openalex.org/C39608478","wikidata":"https://www.wikidata.org/wiki/Q5015979","display_name":"Cache language model","level":5,"score":0.4292064607143402},{"id":"https://openalex.org/C98045186","wikidata":"https://www.wikidata.org/wiki/Q205663","display_name":"Process (computing)","level":2,"score":0.42123907804489136},{"id":"https://openalex.org/C177264268","wikidata":"https://www.wikidata.org/wiki/Q1514741","display_name":"Set (abstract data type)","level":2,"score":0.3899019956588745},{"id":"https://openalex.org/C195324797","wikidata":"https://www.wikidata.org/wiki/Q33742","display_name":"Natural language","level":2,"score":0.1896166205406189},{"id":"https://openalex.org/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","level":1,"score":0.11808302998542786},{"id":"https://openalex.org/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"score":0.11298114061355591},{"id":"https://openalex.org/C83479923","wikidata":"https://www.wikidata.org/wiki/Q2063748","display_name":"Universal Networking Language","level":4,"score":0.07738485932350159},{"id":"https://openalex.org/C120665830","wikidata":"https://www.wikidata.org/wiki/Q14620","display_name":"Optics","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},{"id":"https://openalex.org/C129353971","wikidata":"https://www.wikidata.org/wiki/Q5156949","display_name":"Comprehension approach","level":3,"score":0.0},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/icassp39728.2021.9414158","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icassp39728.2021.9414158","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"ICASSP 2021 - 2021 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":27,"referenced_works":["https://openalex.org/W197277712","https://openalex.org/W2118090838","https://openalex.org/W2251765408","https://openalex.org/W2530571334","https://openalex.org/W2561995736","https://openalex.org/W2741602058","https://openalex.org/W2788353357","https://openalex.org/W2896068220","https://openalex.org/W2937754410","https://openalex.org/W2939408446","https://openalex.org/W2950836278","https://openalex.org/W2963118869","https://openalex.org/W2964266061","https://openalex.org/W2972312617","https://openalex.org/W2972702443","https://openalex.org/W2972954451","https://openalex.org/W2989143494","https://openalex.org/W3015492205","https://openalex.org/W3034430025","https://openalex.org/W3042170933","https://openalex.org/W4299579390","https://openalex.org/W6677518113","https://openalex.org/W6744957266","https://openalex.org/W6748160219","https://openalex.org/W6755736406","https://openalex.org/W6770018436","https://openalex.org/W6780815891"],"related_works":["https://openalex.org/W4255155614","https://openalex.org/W2394860946","https://openalex.org/W761725120","https://openalex.org/W2787311093","https://openalex.org/W2071315630","https://openalex.org/W1508853749","https://openalex.org/W1745277","https://openalex.org/W2009170886","https://openalex.org/W2897427480","https://openalex.org/W2944691285"],"abstract_inverted_index":{"In":[0,37],"the":[1,10,43,55,90,107,121,142,153],"automatic":[2],"speech":[3,14,21,45,78],"recognition":[4,15,22,46,79],"(ASR)":[5],"system,":[6],"how":[7],"to":[8,26,93,114],"solve":[9],"problem":[11],"of":[12,109],"code-switch":[13,44,76,91],"has":[16],"been":[17],"a":[18,67,94,98,128],"concern.":[19],"Code-switch":[20],"is":[23,51,81,112],"challenging":[24],"due":[25],"data":[27,74,110],"scarcity":[28,111],"as":[29,31],"well":[30],"diverse":[32],"syntactic":[33],"structures":[34],"across":[35],"languages.":[36],"this":[38],"paper,":[39],"we":[40],"focus":[41],"on":[42],"in":[47,62,160],"mainland":[48],"China,":[49],"which":[50,80],"obviously":[52],"different":[53],"from":[54,152],"Hong":[56],"Kong":[57],"and":[58,101],"Southeast":[59],"Asia":[60],"area":[61],"linguistic":[63],"characteristics.":[64],"We":[65,139],"propose":[66],"novel":[68],"approach":[69,88,144],"that":[70,132,141],"only":[71],"uses":[72],"monolingual":[73,95,155],"for":[75],"second-pass":[77],"also":[82],"named":[83],"language":[84,102,156],"model":[85,103,157],"rescoring.":[86],"The":[87,117],"converts":[89],"sentence":[92,96],"by":[97,127],"word":[99,118,122,136],"mapping":[100,123],"determination":[104],"step,":[105],"therefore":[106],"issue":[108],"unnecessary":[113],"be":[115],"considered.":[116],"pairs":[119],"during":[120],"step":[124],"are":[125],"generated":[126],"fine-designed":[129],"generation":[130],"process":[131],"incorporates":[133],"machine":[134],"translation,":[135],"alignment,":[137],"etc.":[138],"show":[140],"proposed":[143],"achieves":[145],"an":[146],"over":[147],"7.23%":[148],"relative":[149],"WER":[150],"reduction":[151],"naive":[154],"(MLM)":[158],"rescoring":[159],"our":[161],"test":[162],"set.":[163]},"counts_by_year":[{"year":2025,"cited_by_count":1},{"year":2024,"cited_by_count":3},{"year":2023,"cited_by_count":1},{"year":2022,"cited_by_count":1},{"year":2021,"cited_by_count":1}],"updated_date":"2026-07-14T23:27:15.235271","created_date":"2025-10-10T00:00:00"}