{"id":"https://openalex.org/W106137644","doi":null,"title":"THE SIMILARITY MEASURE AMONG ACOUSTIC MODELS AND ITS TWO APPLICATIONS","display_name":"THE SIMILARITY MEASURE AMONG ACOUSTIC MODELS AND ITS TWO APPLICATIONS","publication_year":1998,"publication_date":"1998-01-01","ids":{"openalex":"https://openalex.org/W106137644","mag":"106137644"},"language":"en","primary_location":{"id":"pmh:oai:CiteSeerX.psu:10.1.1.329.8395","doi":null,"is_oa":false,"landing_page_url":"http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.329.8395","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"http://cslt.riit.tsinghua.edu.cn/~fzheng/PAPERS/1998/9812E_ISCSLP_AMSIMILARITY_WJ(ZF).pdf","raw_type":"text"},"volume":null,"type":"article","is_traditional":true,"indexed_in":[],"open_access":{"is_oa":false,"oa_status":"closed","oa_url":null,"any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":null,"display_name":"Jian Wu","orcid":"https://orcid.org/0000-0002-3394-1507","observed_orcids":["https://orcid.org/0000-0002-3394-1507"]},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Jian Wu","raw_affiliation_strings":[],"raw_orcid":"https://orcid.org/0000-0002-3394-1507","affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5082058381","display_name":"Wenhu Wu","orcid":null,"observed_orcids":[]},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Wenhu Wu","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5111519727","display_name":"Ditang Fang","orcid":null,"observed_orcids":[]},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Ditang Fang","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":0,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.0,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":null,"last_page":null},"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/T10860","display_name":"Speech and Audio Processing","score":0.0003000000142492354,"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"}},{"id":"https://openalex.org/T10403","display_name":"Phonetics and Phonology Research","score":9.999999747378752e-05,"subfield":{"id":"https://openalex.org/subfields/3205","display_name":"Experimental and Cognitive Psychology"},"field":{"id":"https://openalex.org/fields/32","display_name":"Psychology"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/similarity-measures","display_name":"similarity measures","score":0.8149999976158142},{"id":"https://openalex.org/keywords/acoustic-modeling","display_name":"acoustic modeling","score":0.921999990940094},{"id":"https://openalex.org/keywords/speech-recognition","display_name":"speech recognition","score":0.9380000233650208},{"id":"https://openalex.org/keywords/model-availability","display_name":"model availability","score":0.5709999799728394}],"concepts":[{"id":"https://openalex.org/C23224414","wikidata":"https://www.wikidata.org/wiki/Q176769","display_name":"Hidden Markov model","level":2,"score":0.7103976011276245},{"id":"https://openalex.org/C2780009758","wikidata":"https://www.wikidata.org/wiki/Q6804172","display_name":"Measure (data warehouse)","level":2,"score":0.6897865533828735},{"id":"https://openalex.org/C2639959","wikidata":"https://www.wikidata.org/wiki/Q1344778","display_name":"Distance measures","level":2,"score":0.6045607924461365},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5863528251647949},{"id":"https://openalex.org/C2776517306","wikidata":"https://www.wikidata.org/wiki/Q29017317","display_name":"Similarity measure","level":2,"score":0.538864016532898},{"id":"https://openalex.org/C28490314","wikidata":"https://www.wikidata.org/wiki/Q189436","display_name":"Speech recognition","level":1,"score":0.5075737237930298},{"id":"https://openalex.org/C103278499","wikidata":"https://www.wikidata.org/wiki/Q254465","display_name":"Similarity (geometry)","level":3,"score":0.4707622826099396},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.4460999667644501},{"id":"https://openalex.org/C25343380","wikidata":"https://www.wikidata.org/wiki/Q277521","display_name":"Relation (database)","level":2,"score":0.423747718334198},{"id":"https://openalex.org/C45374587","wikidata":"https://www.wikidata.org/wiki/Q12525525","display_name":"Computation","level":2,"score":0.4122401475906372},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.41035354137420654},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.3598238229751587},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.2696723937988281},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.26876839995384216},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.0}],"mesh":[],"locations_count":4,"locations":[{"id":"pmh:oai:CiteSeerX.psu:10.1.1.329.8395","doi":null,"is_oa":false,"landing_page_url":"http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.329.8395","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"http://cslt.riit.tsinghua.edu.cn/~fzheng/PAPERS/1998/9812E_ISCSLP_AMSIMILARITY_WJ(ZF).pdf","raw_type":"text"},{"id":"pmh:oai:CiteSeerX.psu:10.1.1.330.4869","doi":null,"is_oa":false,"landing_page_url":"http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.330.4869","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"http://www.isca-speech.org/archive_open/archive_papers/iscslp1998/ASR-B3.pdf","raw_type":"text"},{"id":"pmh:oai:CiteSeerX.psu:10.1.1.628.615","doi":null,"is_oa":false,"landing_page_url":"http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.628.615","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"http://www.colips.org/conference/iscslp2006/anthology/1998/papers/asr-b3.pdf","raw_type":"text"},{"id":"mag:106137644","doi":null,"is_oa":false,"landing_page_url":"http://cslt.riit.tsinghua.edu.cn/~fzheng/PAPERS/1998/9812E_ISCSLP_AMSIMILARITY_WJ(ZF).pdf","pdf_url":null,"source":null,"license":null,"license_id":null,"version":null,"is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":null}],"best_oa_location":null,"sustainable_development_goals":[],"study_designs":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":13,"referenced_works":["https://openalex.org/W1575431606","https://openalex.org/W1808473778","https://openalex.org/W1877570817","https://openalex.org/W1991133427","https://openalex.org/W2020127877","https://openalex.org/W2021760654","https://openalex.org/W2049633694","https://openalex.org/W2075978670","https://openalex.org/W2102845714","https://openalex.org/W2111751470","https://openalex.org/W2112197391","https://openalex.org/W2121178390","https://openalex.org/W2141913457"],"related_works":["https://openalex.org/W7099725856","https://openalex.org/W4254174576","https://openalex.org/W1654807615","https://openalex.org/W2980286501","https://openalex.org/W1656766959","https://openalex.org/W3140155973","https://openalex.org/W2128011037","https://openalex.org/W163903552","https://openalex.org/W7098590888","https://openalex.org/W2467500531"],"abstract_inverted_index":{"The":[0],"distance":[1,20,42,60,80,90,147],"measure":[2,43,91,148],"of":[3,14,36,54,78,104,129,146],"two":[4,22,38,151],"stochastic":[5,15,82],"processes":[6],"is":[7,100,115],"a":[8,88],"key":[9],"problem":[10],"in":[11],"the":[12,19,28,31,34,41,46,51,59,75,79,118,121,159],"processing":[13],"signals.In":[16],"speech":[17,156],"recognition,":[18],"between":[21,61,81],"basic":[23,62],"recognition":[24,55],"models":[25,131],"can":[26,44,49,123],"provide":[27],"information":[29],"about":[30],"relation":[32],"and":[33,149],"difference":[35],"these":[37],"units.In":[39],"fact,":[40],"depict":[45],"model\u2019s":[47],"availability.We":[48],"improve":[50],"hit":[52],"rate":[53],"results":[56],"by":[57],"adjusting":[58],"unit":[63],"models.In":[64],"recent":[65],"years,":[66],"many":[67],"definitions":[68],"have":[69,86],"been":[70],"put":[71],"forward":[72],"for":[73],"calculating":[74],"exact":[76],"value":[77],"processes.":[83],"We":[84],"also":[85],"developed":[87],"simplified":[89,144],"based":[92],"on":[93,142],"CDCPM":[94],"(Center-Distance":[95,112],"Continuous":[96],"Probability":[97],"Model)":[98],"which":[99],"an":[101],"improved":[102],"version":[103],"CHMM":[105],"(Continuous":[106],"Hidden":[107],"Markov":[108],"Model).And":[109],"since":[110],"CDN":[111],"Normal)":[113],"distribution":[114],"derived":[116],"from":[117],"normal":[119],"distribution,":[120],"definition":[122,145],"be":[124],"extended":[125],"to":[126,154],"other":[127],"types":[128],"acoustic":[130],"such":[132],"as":[133],"Segmental":[134],"HMM":[135],"easily.In":[136],"this":[137,143],"paper,":[138],"we":[139],"will":[140],"focus":[141],"propose":[150],"examples":[152],"applied":[153],"continuous":[155],"recognition.":[157],"And":[158],"experiment":[160],"result":[161],"shows":[162],"it":[163],"preserve":[164],"very":[165],"good":[166],"performance":[167],"without":[168],"additory":[169],"computation.":[170],"1.":[171],"INTRODUCTION":[172],"TO":[173]},"counts_by_year":[],"updated_date":"2026-11-11T12:16:26.678958","created_date":"2016-06-24T00:00:00"}
