{"id":"https://openalex.org/W2131556841","doi":"https://doi.org/10.1109/iceei.2011.6021790","title":"Out of vocabulary detection in Indonesian speech recognition using word and syllable level decoding","display_name":"Out of vocabulary detection in Indonesian speech recognition using word and syllable level decoding","publication_year":2011,"publication_date":"2011-07-01","ids":{"openalex":"https://openalex.org/W2131556841","doi":"https://doi.org/10.1109/iceei.2011.6021790","mag":"2131556841"},"language":"en","primary_location":{"id":"doi:10.1109/iceei.2011.6021790","is_oa":false,"landing_page_url":"https://doi.org/10.1109/iceei.2011.6021790","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 2011 International Conference on Electrical Engineering and Informatics","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/A5069511887","display_name":"Aswin Juari","orcid":null},"institutions":[{"id":"https://openalex.org/I134635517","display_name":"Bandung Institute of Technology","ror":"https://ror.org/00apj8t60","country_code":"ID","type":"education","lineage":["https://openalex.org/I134635517"]}],"countries":["ID"],"is_corresponding":true,"raw_author_name":"Aswin Juari","raw_affiliation_strings":["Informatic Department, Institut Teknologi Bandung, Indonesia"],"affiliations":[{"raw_affiliation_string":"Informatic Department, Institut Teknologi Bandung, Indonesia","institution_ids":["https://openalex.org/I134635517"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5021128017","display_name":"Ayu Purwarianti","orcid":"https://orcid.org/0000-0002-5016-3700"},"institutions":[{"id":"https://openalex.org/I134635517","display_name":"Bandung Institute of Technology","ror":"https://ror.org/00apj8t60","country_code":"ID","type":"education","lineage":["https://openalex.org/I134635517"]}],"countries":["ID"],"is_corresponding":false,"raw_author_name":"Ayu Purwarianti","raw_affiliation_strings":["Informatic Department, Institut Teknologi Bandung, Indonesia"],"affiliations":[{"raw_affiliation_string":"Informatic Department, Institut Teknologi Bandung, Indonesia","institution_ids":["https://openalex.org/I134635517"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5069511887"],"corresponding_institution_ids":["https://openalex.org/I134635517"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.12899131,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"8"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12031","display_name":"Speech and dialogue systems","score":0.9945999979972839,"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/T12031","display_name":"Speech and dialogue systems","score":0.9945999979972839,"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/T10201","display_name":"Speech Recognition and Synthesis","score":0.9936000108718872,"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/T11398","display_name":"Hand Gesture Recognition Systems","score":0.9713000059127808,"subfield":{"id":"https://openalex.org/subfields/1709","display_name":"Human-Computer Interaction"},"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":0.813511848449707},{"id":"https://openalex.org/keywords/speech-recognition","display_name":"Speech recognition","score":0.809951901435852},{"id":"https://openalex.org/keywords/decoding-methods","display_name":"Decoding methods","score":0.7448087930679321},{"id":"https://openalex.org/keywords/syllable","display_name":"Syllable","score":0.7089894413948059},{"id":"https://openalex.org/keywords/word-error-rate","display_name":"Word error rate","score":0.6833734512329102},{"id":"https://openalex.org/keywords/word","display_name":"Word (group theory)","score":0.590787947177887},{"id":"https://openalex.org/keywords/vocabulary","display_name":"Vocabulary","score":0.5880195498466492},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5627747178077698},{"id":"https://openalex.org/keywords/natural-language-processing","display_name":"Natural language processing","score":0.49527159333229065},{"id":"https://openalex.org/keywords/linguistics","display_name":"Linguistics","score":0.10214632749557495},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.07456281781196594}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.813511848449707},{"id":"https://openalex.org/C28490314","wikidata":"https://www.wikidata.org/wiki/Q189436","display_name":"Speech recognition","level":1,"score":0.809951901435852},{"id":"https://openalex.org/C57273362","wikidata":"https://www.wikidata.org/wiki/Q576722","display_name":"Decoding methods","level":2,"score":0.7448087930679321},{"id":"https://openalex.org/C109089402","wikidata":"https://www.wikidata.org/wiki/Q8188","display_name":"Syllable","level":2,"score":0.7089894413948059},{"id":"https://openalex.org/C40969351","wikidata":"https://www.wikidata.org/wiki/Q3516228","display_name":"Word error rate","level":2,"score":0.6833734512329102},{"id":"https://openalex.org/C90805587","wikidata":"https://www.wikidata.org/wiki/Q10944557","display_name":"Word (group theory)","level":2,"score":0.590787947177887},{"id":"https://openalex.org/C2777601683","wikidata":"https://www.wikidata.org/wiki/Q6499736","display_name":"Vocabulary","level":2,"score":0.5880195498466492},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5627747178077698},{"id":"https://openalex.org/C204321447","wikidata":"https://www.wikidata.org/wiki/Q30642","display_name":"Natural language processing","level":1,"score":0.49527159333229065},{"id":"https://openalex.org/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","level":1,"score":0.10214632749557495},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.07456281781196594},{"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/iceei.2011.6021790","is_oa":false,"landing_page_url":"https://doi.org/10.1109/iceei.2011.6021790","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 2011 International Conference on Electrical Engineering and Informatics","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.6200000047683716,"display_name":"Quality Education","id":"https://metadata.un.org/sdg/4"}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":15,"referenced_works":["https://openalex.org/W58893626","https://openalex.org/W72347498","https://openalex.org/W77114827","https://openalex.org/W1501139663","https://openalex.org/W1549285799","https://openalex.org/W2052384514","https://openalex.org/W2118835780","https://openalex.org/W2125838338","https://openalex.org/W2465979459","https://openalex.org/W2547039119","https://openalex.org/W4244350465","https://openalex.org/W6602415096","https://openalex.org/W6602935006","https://openalex.org/W6728823536","https://openalex.org/W7039088390"],"related_works":["https://openalex.org/W2161474341","https://openalex.org/W4302615923","https://openalex.org/W3203142394","https://openalex.org/W2351061015","https://openalex.org/W4220731478","https://openalex.org/W1997182898","https://openalex.org/W2061937230","https://openalex.org/W2132658536","https://openalex.org/W50892825","https://openalex.org/W2944691285"],"abstract_inverted_index":{"One":[0],"of":[1,9,21,56],"the":[2,25,68,104],"problems":[3],"in":[4,49],"speech":[5,32,65,138],"recognition":[6,109],"is":[7,36,47,67,74,111,117,141],"out":[8],"vocabulary":[10,22],"words":[11,18,23,26,105],"(OOV)":[12],"because":[13,34,55],"they":[14],"can":[15],"make":[16],"some":[17,84],"error.":[19],"Out":[20],"are":[24,98,106],"that":[27,133],"cannot":[28],"be":[29],"recognized":[30],"by":[31,134,143],"recognizer":[33,66,139],"there":[35],"no":[37],"recognizing":[38],"database.":[39],"Alignment,":[40],"language":[41,94],"model,":[42],"and":[43,60,78,88,96,127],"POS":[44],"Tag":[45],"method":[46],"proposed":[48],"order":[50],"to":[51,76,82,101],"recognize":[52],"word":[53,77,87],"error":[54],"OOV":[57,115,120,136],"words.":[58],"Word":[59],"syllable":[61,79,89],"level":[62,80,90],"decoding":[63,81],"from":[64,86],"input":[69],"for":[70],"this":[71],"method.":[72],"Alignment":[73],"applied":[75,100],"get":[83],"differences":[85],"decoding.":[91],"After":[92],"that,":[93],"model":[95],"tag":[97],"also":[99,131],"determine":[102],"if":[103,114],"correct.":[107],"Speech":[108],"accuracy":[110,140],"about":[112,124],"75%":[113,128],"rate":[116],"15,5%.":[118],"The":[119],"detection":[121],"process":[122],"reaches":[123],"87%":[125],"precision":[126],"recall.":[129],"Experiments":[130],"show":[132],"using":[135],"detection,":[137],"increased":[142],"11%.":[144]},"counts_by_year":[],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
