{"id":"https://openalex.org/W2895880548","doi":"https://doi.org/10.1145/3207677.3277918","title":"Keyword Spotting Based on Hypothesis Boundary Realignment and State-Level Confidence Weighting","display_name":"Keyword Spotting Based on Hypothesis Boundary Realignment and State-Level Confidence Weighting","publication_year":2018,"publication_date":"2018-10-18","ids":{"openalex":"https://openalex.org/W2895880548","doi":"https://doi.org/10.1145/3207677.3277918","mag":"2895880548"},"language":"en","primary_location":{"id":"doi:10.1145/3207677.3277918","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3207677.3277918","pdf_url":null,"source":{"id":"https://openalex.org/S4306523741","display_name":"Proceedings of the 2nd International Conference on Computer Science and Application Engineering","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 2nd International Conference on Computer Science and Application Engineering","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/A5100410286","display_name":"Hong Liu","orcid":"https://orcid.org/0000-0002-0896-8409"},"institutions":[{"id":"https://openalex.org/I20231570","display_name":"Peking University","ror":"https://ror.org/02v51f717","country_code":"CN","type":"education","lineage":["https://openalex.org/I20231570"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Hong Liu","raw_affiliation_strings":["Key Laboratory of Machine Perception, Shenzhen Graduate School, Peking University, China"],"affiliations":[{"raw_affiliation_string":"Key Laboratory of Machine Perception, Shenzhen Graduate School, Peking University, China","institution_ids":["https://openalex.org/I20231570"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5083084298","display_name":"Yuezhao Chen","orcid":null},"institutions":[{"id":"https://openalex.org/I20231570","display_name":"Peking University","ror":"https://ror.org/02v51f717","country_code":"CN","type":"education","lineage":["https://openalex.org/I20231570"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yuezhao Chen","raw_affiliation_strings":["Key Laboratory of Machine Perception, Shenzhen Graduate School, Peking University, China"],"affiliations":[{"raw_affiliation_string":"Key Laboratory of Machine Perception, Shenzhen Graduate School, Peking University, China","institution_ids":["https://openalex.org/I20231570"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5038044561","display_name":"Runwei Ding","orcid":"https://orcid.org/0000-0003-4987-0405"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Runwei Ding","raw_affiliation_strings":["Shenzhen Touching AI Technologies Co., Ltd, China"],"affiliations":[{"raw_affiliation_string":"Shenzhen Touching AI Technologies Co., Ltd, China","institution_ids":[]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5101483071","display_name":"Cheng Pang","orcid":"https://orcid.org/0000-0001-9631-3658"},"institutions":[{"id":"https://openalex.org/I20231570","display_name":"Peking University","ror":"https://ror.org/02v51f717","country_code":"CN","type":"education","lineage":["https://openalex.org/I20231570"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Cheng Pang","raw_affiliation_strings":["Key Laboratory of Machine Perception, Shenzhen Graduate School, Peking University, China"],"affiliations":[{"raw_affiliation_string":"Key Laboratory of Machine Perception, Shenzhen Graduate School, Peking University, China","institution_ids":["https://openalex.org/I20231570"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5100410286"],"corresponding_institution_ids":["https://openalex.org/I20231570"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.12560096,"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":"7"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10201","display_name":"Speech Recognition and Synthesis","score":0.9965000152587891,"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":0.9965000152587891,"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/T11550","display_name":"Text and Document Classification Technologies","score":0.9825000166893005,"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":0.975600004196167,"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/keyword-spotting","display_name":"Keyword spotting","score":0.9138604402542114},{"id":"https://openalex.org/keywords/weighting","display_name":"Weighting","score":0.7533146142959595},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7260924577713013},{"id":"https://openalex.org/keywords/spotting","display_name":"Spotting","score":0.585103452205658},{"id":"https://openalex.org/keywords/false-alarm","display_name":"False alarm","score":0.5683903098106384},{"id":"https://openalex.org/keywords/hidden-markov-model","display_name":"Hidden Markov model","score":0.5412594079971313},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.4931935667991638},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.47537103295326233},{"id":"https://openalex.org/keywords/speech-recognition","display_name":"Speech recognition","score":0.42264100909233093},{"id":"https://openalex.org/keywords/boundary","display_name":"Boundary (topology)","score":0.4184038043022156},{"id":"https://openalex.org/keywords/flexibility","display_name":"Flexibility (engineering)","score":0.4182726740837097},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.23481526970863342},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.1732158064842224}],"concepts":[{"id":"https://openalex.org/C2781213101","wikidata":"https://www.wikidata.org/wiki/Q6398558","display_name":"Keyword spotting","level":2,"score":0.9138604402542114},{"id":"https://openalex.org/C183115368","wikidata":"https://www.wikidata.org/wiki/Q856577","display_name":"Weighting","level":2,"score":0.7533146142959595},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7260924577713013},{"id":"https://openalex.org/C2779506182","wikidata":"https://www.wikidata.org/wiki/Q7580141","display_name":"Spotting","level":2,"score":0.585103452205658},{"id":"https://openalex.org/C2776836416","wikidata":"https://www.wikidata.org/wiki/Q1364844","display_name":"False alarm","level":2,"score":0.5683903098106384},{"id":"https://openalex.org/C23224414","wikidata":"https://www.wikidata.org/wiki/Q176769","display_name":"Hidden Markov model","level":2,"score":0.5412594079971313},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4931935667991638},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.47537103295326233},{"id":"https://openalex.org/C28490314","wikidata":"https://www.wikidata.org/wiki/Q189436","display_name":"Speech recognition","level":1,"score":0.42264100909233093},{"id":"https://openalex.org/C62354387","wikidata":"https://www.wikidata.org/wiki/Q875399","display_name":"Boundary (topology)","level":2,"score":0.4184038043022156},{"id":"https://openalex.org/C2780598303","wikidata":"https://www.wikidata.org/wiki/Q65921492","display_name":"Flexibility (engineering)","level":2,"score":0.4182726740837097},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.23481526970863342},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.1732158064842224},{"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/C126838900","wikidata":"https://www.wikidata.org/wiki/Q77604","display_name":"Radiology","level":1,"score":0.0},{"id":"https://openalex.org/C71924100","wikidata":"https://www.wikidata.org/wiki/Q11190","display_name":"Medicine","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3207677.3277918","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3207677.3277918","pdf_url":null,"source":{"id":"https://openalex.org/S4306523741","display_name":"Proceedings of the 2nd International Conference on Computer Science and Application Engineering","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 2nd International Conference on Computer Science and Application Engineering","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Peace, Justice and strong institutions","score":0.6899999976158142,"id":"https://metadata.un.org/sdg/16"}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":27,"referenced_works":["https://openalex.org/W23025778","https://openalex.org/W114193738","https://openalex.org/W210770835","https://openalex.org/W1565198967","https://openalex.org/W1974205368","https://openalex.org/W2009782887","https://openalex.org/W2015688877","https://openalex.org/W2021556273","https://openalex.org/W2034940213","https://openalex.org/W2043422002","https://openalex.org/W2056986588","https://openalex.org/W2077804127","https://openalex.org/W2086267546","https://openalex.org/W2103371184","https://openalex.org/W2108932455","https://openalex.org/W2116961747","https://openalex.org/W2122797512","https://openalex.org/W2128833328","https://openalex.org/W2142806759","https://openalex.org/W2145986087","https://openalex.org/W2168119002","https://openalex.org/W2396838512","https://openalex.org/W2404329556","https://openalex.org/W2442329935","https://openalex.org/W2671812860","https://openalex.org/W2783652918","https://openalex.org/W4206508928"],"related_works":["https://openalex.org/W2918559346","https://openalex.org/W2114097550","https://openalex.org/W4286904253","https://openalex.org/W3119978414","https://openalex.org/W2516975559","https://openalex.org/W2388033618","https://openalex.org/W2545741539","https://openalex.org/W3206647229","https://openalex.org/W1969408022","https://openalex.org/W2000885660"],"abstract_inverted_index":{"Keyword1":[0],"spotting":[1],"(KWS)":[2],"deals":[3],"with":[4],"the":[5,19,43,52,59,119,131,144,149,153],"identification":[6],"of":[7],"keywords":[8],"in":[9,38,51],"speech":[10],"utterances.":[11],"A":[12],"two-stage":[13],"approach":[14],"is":[15,45,56,76,96,112,127,141],"often":[16],"used":[17,97],"for":[18,86,104],"flexibility":[20],"and":[21,32,48,143],"high":[22],"efficiency.":[23],"The":[24],"two":[25,80,150],"stages":[26],"are":[27],"keyword":[28],"hypotheses":[29],"detection":[30],"stage":[31,37],"hit":[33],"or":[34],"false-alarm":[35],"verification":[36,53],"sequence.":[39],"How":[40],"to":[41,98,114,129],"reduce":[42],"false-alarms":[44],"a":[46,67,91,122],"key":[47],"difficult":[49],"problem":[50],"stage,":[54],"which":[55],"formatted":[57],"as":[58],"confidence":[60,89,124],"measure":[61],"(CM)":[62],"problem.":[63],"In":[64],"this":[65,116],"paper,":[66],"novel":[68],"keyword-filler":[69],"hidden":[70],"Markov":[71],"model":[72],"(HMM)":[73],"based":[74,78,134,147],"method":[75,95,126,146],"proposed":[77,128,145],"on":[79,148],"improved":[81],"approaches.":[82],"On":[83,118],"one":[84],"hand,":[85,121],"more":[87,100],"effective":[88],"measure,":[90],"hypothesis":[92],"boundary":[93],"realignment":[94],"gain":[99],"precise":[101],"hypothesized":[102],"segments":[103],"possible":[105],"keyword.":[106],"Then":[107],"an":[108],"overlap":[109],"ratio":[110],"criterion":[111],"defined":[113],"evaluate":[115],"process.":[117],"other":[120],"state-level":[123],"weighting":[125],"improve":[130],"posterior":[132],"probability":[133],"CM.":[135],"Experiments":[136],"show":[137],"that":[138],"either":[139],"improvement":[140],"effective,":[142],"processes":[151],"gives":[152],"best":[154],"performance.":[155]},"counts_by_year":[],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}