{"id":"https://openalex.org/W71224604","doi":"https://doi.org/10.21437/eurospeech.1997-29","title":"Automatic architecture design by likelihood-based context clustering with crossvalidation","display_name":"Automatic architecture design by likelihood-based context clustering with crossvalidation","publication_year":1997,"publication_date":"1997-09-22","ids":{"openalex":"https://openalex.org/W71224604","doi":"https://doi.org/10.21437/eurospeech.1997-29","mag":"71224604"},"language":"en","primary_location":{"id":"doi:10.21437/eurospeech.1997-29","is_oa":false,"landing_page_url":"https://doi.org/10.21437/eurospeech.1997-29","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"5th European Conference on Speech Communication and Technology (Eurospeech 1997)","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/A5026494927","display_name":"Ivica Rogina","orcid":null},"institutions":[{"id":"https://openalex.org/I102335020","display_name":"Karlsruhe Institute of Technology","ror":"https://ror.org/04t3en479","country_code":"DE","type":"education","lineage":["https://openalex.org/I102335020","https://openalex.org/I1305996414"]}],"countries":["DE"],"is_corresponding":true,"raw_author_name":"Ivica Rogina","raw_affiliation_strings":["Interactive Systems Labs University of Karlsruhe, Am Fasanengarten 5, 76131 Karlsruhe, Germany"],"affiliations":[{"raw_affiliation_string":"Interactive Systems Labs University of Karlsruhe, Am Fasanengarten 5, 76131 Karlsruhe, Germany","institution_ids":["https://openalex.org/I102335020"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":["https://openalex.org/A5026494927"],"corresponding_institution_ids":["https://openalex.org/I102335020"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":10,"citation_normalized_percentile":{"value":0.01277761,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"1223","last_page":"1226"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11309","display_name":"Music and Audio Processing","score":0.9994999766349792,"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"}},"topics":[{"id":"https://openalex.org/T11309","display_name":"Music and Audio Processing","score":0.9994999766349792,"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/T10201","display_name":"Speech Recognition and Synthesis","score":0.9966999888420105,"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":0.9929999709129333,"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/computer-science","display_name":"Computer science","score":0.738075315952301},{"id":"https://openalex.org/keywords/cluster-analysis","display_name":"Cluster analysis","score":0.6598986983299255},{"id":"https://openalex.org/keywords/entropy","display_name":"Entropy (arrow of time)","score":0.524256706237793},{"id":"https://openalex.org/keywords/decision-tree","display_name":"Decision tree","score":0.5083851218223572},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.46886876225471497},{"id":"https://openalex.org/keywords/measure","display_name":"Measure (data warehouse)","score":0.4644570052623749},{"id":"https://openalex.org/keywords/context","display_name":"Context (archaeology)","score":0.45406243205070496},{"id":"https://openalex.org/keywords/context-model","display_name":"Context model","score":0.42999333143234253},{"id":"https://openalex.org/keywords/principle-of-maximum-entropy","display_name":"Principle of maximum entropy","score":0.4177100658416748},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.40742895007133484},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.39930418133735657},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.3512035012245178}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.738075315952301},{"id":"https://openalex.org/C73555534","wikidata":"https://www.wikidata.org/wiki/Q622825","display_name":"Cluster analysis","level":2,"score":0.6598986983299255},{"id":"https://openalex.org/C106301342","wikidata":"https://www.wikidata.org/wiki/Q4117933","display_name":"Entropy (arrow of time)","level":2,"score":0.524256706237793},{"id":"https://openalex.org/C84525736","wikidata":"https://www.wikidata.org/wiki/Q831366","display_name":"Decision tree","level":2,"score":0.5083851218223572},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.46886876225471497},{"id":"https://openalex.org/C2780009758","wikidata":"https://www.wikidata.org/wiki/Q6804172","display_name":"Measure (data warehouse)","level":2,"score":0.4644570052623749},{"id":"https://openalex.org/C2779343474","wikidata":"https://www.wikidata.org/wiki/Q3109175","display_name":"Context (archaeology)","level":2,"score":0.45406243205070496},{"id":"https://openalex.org/C183322885","wikidata":"https://www.wikidata.org/wiki/Q17007702","display_name":"Context model","level":3,"score":0.42999333143234253},{"id":"https://openalex.org/C9679016","wikidata":"https://www.wikidata.org/wiki/Q1417473","display_name":"Principle of maximum entropy","level":2,"score":0.4177100658416748},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.40742895007133484},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.39930418133735657},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.3512035012245178},{"id":"https://openalex.org/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","level":0,"score":0.0},{"id":"https://openalex.org/C2781238097","wikidata":"https://www.wikidata.org/wiki/Q175026","display_name":"Object (grammar)","level":2,"score":0.0},{"id":"https://openalex.org/C62520636","wikidata":"https://www.wikidata.org/wiki/Q944","display_name":"Quantum mechanics","level":1,"score":0.0},{"id":"https://openalex.org/C151730666","wikidata":"https://www.wikidata.org/wiki/Q7205","display_name":"Paleontology","level":1,"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":3,"locations":[{"id":"doi:10.21437/eurospeech.1997-29","is_oa":false,"landing_page_url":"https://doi.org/10.21437/eurospeech.1997-29","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"5th European Conference on Speech Communication and Technology (Eurospeech 1997)","raw_type":"proceedings-article"},{"id":"pmh:oai:CiteSeerX.psu:10.1.1.30.3748","is_oa":false,"landing_page_url":"http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.30.3748","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"http://werner.ira.uka.de/~wwwadm/papers/speech/EUROSPEECH97/EUROSPEECH97-ivica.ps.gz","raw_type":"text"},{"id":"pmh:oai:EVASTAR-Karlsruhe.de:185297","is_oa":false,"landing_page_url":"https://publikationen.bibliothek.kit.edu/185297","pdf_url":null,"source":{"id":"https://openalex.org/S4306401992","display_name":"Repository KITopen (Karlsruhe Institute of Technology)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I102335020","host_organization_name":"Karlsruhe Institute of Technology","host_organization_lineage":["https://openalex.org/I102335020"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"","raw_type":"doc-type:bookPart"}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.5099999904632568,"id":"https://metadata.un.org/sdg/11","display_name":"Sustainable cities and communities"}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":6,"referenced_works":["https://openalex.org/W1535702289","https://openalex.org/W1644467064","https://openalex.org/W2097203679","https://openalex.org/W2152439927","https://openalex.org/W2276283915","https://openalex.org/W3144707434"],"related_works":["https://openalex.org/W4298130764","https://openalex.org/W2804364458","https://openalex.org/W2132641928","https://openalex.org/W4310225030","https://openalex.org/W2090259340","https://openalex.org/W1926736923","https://openalex.org/W2393816671","https://openalex.org/W2158836806","https://openalex.org/W3041490575","https://openalex.org/W2970690932"],"abstract_inverted_index":{"Most":[0],"state-of-the-art":[1],"speech":[2,139],"recognizers":[3,140],"benefit":[4],"from":[5],"some":[6],"kind":[7],"of":[8,41,52,97,103],"context":[9,21],"information":[10],"in":[11,133,149],"their":[12],"acoustic":[13],"modeling":[14],"[1][2][3].":[15],"The":[16,34],"most":[17],"common":[18],"approach":[19],"to":[20,37],"clustering":[22],"is":[23,28,44],"a":[24,75,89,104],"divisive":[25],"method":[26],"that":[27,55,78,93,120],"iteratively":[29],"building":[30],"decision":[31,105],"trees":[32],"[4][5].":[33],"problem,":[35],"when":[36],"stop":[38],"the":[39,42,49,60,95,113,134,143,151],"growing":[40],"tree":[43,106],"usually":[45],"solved":[46],"by":[47,59],"choosing":[48],"maximum":[50],"number":[51],"resulting":[53],"models":[54],"can":[56],"be":[57,147],"supported":[58],"available":[61,138],"training":[62],"data":[63],"and/or":[64],"computer":[65],"memory":[66],"and":[67,118],"CPU":[68],"power.":[69],"In":[70],"this":[71],"paper":[72],"we":[73],"propose":[74],"new":[76],"algorithm,":[77],"not":[79],"only":[80],"offers":[81],"an":[82,123,126],"optimized":[83],"stopping":[84],"criterion,":[85],"but":[86],"also":[87],"uses":[88],"likelihood-based":[90],"distance":[91,128],"measure":[92],"optimizes":[94],"likelihood":[96],"unseen":[98],"training-data":[99],"at":[100],"every":[101],"splitting":[102],"node.":[107],"We":[108],"evaluate":[109],"our":[110],"algorithm":[111,124],"on":[112],"Wall":[114],"Street":[115],"Journal":[116],"task,":[117],"show":[119],"it":[121],"outperforms":[122],"using":[125],"entropy-based":[127],"measure.":[129],"1.":[130],"INTRODUCTION":[131],"When":[132],"near":[135],"future":[136],"commercially":[137],"will":[141,146],"hit":[142],"market,":[144],"customers":[145],"interested":[148],"adjusting":[150],"product":[152],"...":[153]},"counts_by_year":[],"updated_date":"2026-04-05T17:49:38.594831","created_date":"2025-10-10T00:00:00"}