{"id":"https://openalex.org/W2183072182","doi":"https://doi.org/10.1109/icmlc.2015.7340952","title":"Piecewise linear high-order hidden Markov models and applications to speech recognition","display_name":"Piecewise linear high-order hidden Markov models and applications to speech recognition","publication_year":2015,"publication_date":"2015-07-01","ids":{"openalex":"https://openalex.org/W2183072182","doi":"https://doi.org/10.1109/icmlc.2015.7340952","mag":"2183072182"},"language":"en","primary_location":{"id":"doi:10.1109/icmlc.2015.7340952","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icmlc.2015.7340952","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2015 International Conference on Machine Learning and Cybernetics (ICMLC)","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/A5082356276","display_name":"Lee-Min Lee","orcid":null},"institutions":[{"id":"https://openalex.org/I130510345","display_name":"Dayeh University","ror":"https://ror.org/03c6e8r26","country_code":"TW","type":"education","lineage":["https://openalex.org/I130510345"]}],"countries":["TW"],"is_corresponding":true,"raw_author_name":"Lee-Min Lee","raw_affiliation_strings":["Department of Electrical Engineering, Da-Yeh University, Changhua, Taiwan"],"affiliations":[{"raw_affiliation_string":"Department of Electrical Engineering, Da-Yeh University, Changhua, Taiwan","institution_ids":["https://openalex.org/I130510345"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":["https://openalex.org/A5082356276"],"corresponding_institution_ids":["https://openalex.org/I130510345"],"apc_list":null,"apc_paid":null,"fwci":0.8629,"has_fulltext":false,"cited_by_count":2,"citation_normalized_percentile":{"value":0.82621022,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":94,"max":96},"biblio":{"volume":null,"issue":null,"first_page":"383","last_page":"388"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10201","display_name":"Speech Recognition and Synthesis","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"}},"topics":[{"id":"https://openalex.org/T10201","display_name":"Speech Recognition and Synthesis","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/T10860","display_name":"Speech and Audio Processing","score":0.995199978351593,"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/T11309","display_name":"Music and Audio Processing","score":0.963100016117096,"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/hidden-markov-model","display_name":"Hidden Markov model","score":0.8745709657669067},{"id":"https://openalex.org/keywords/hidden-semi-markov-model","display_name":"Hidden semi-Markov model","score":0.7941875457763672},{"id":"https://openalex.org/keywords/forward-algorithm","display_name":"Forward algorithm","score":0.7360222339630127},{"id":"https://openalex.org/keywords/maximum-entropy-markov-model","display_name":"Maximum-entropy Markov model","score":0.6781983375549316},{"id":"https://openalex.org/keywords/markov-model","display_name":"Markov model","score":0.6211305260658264},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6105280518531799},{"id":"https://openalex.org/keywords/piecewise","display_name":"Piecewise","score":0.558782696723938},{"id":"https://openalex.org/keywords/variable-order-markov-model","display_name":"Variable-order Markov model","score":0.5346108675003052},{"id":"https://openalex.org/keywords/speech-recognition","display_name":"Speech recognition","score":0.5305212736129761},{"id":"https://openalex.org/keywords/markov-process","display_name":"Markov process","score":0.5004293918609619},{"id":"https://openalex.org/keywords/conditional-independence","display_name":"Conditional independence","score":0.43523308634757996},{"id":"https://openalex.org/keywords/independence","display_name":"Independence (probability theory)","score":0.43153178691864014},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.4249381422996521},{"id":"https://openalex.org/keywords/sequence-labeling","display_name":"Sequence labeling","score":0.4171736240386963},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.39400625228881836},{"id":"https://openalex.org/keywords/markov-chain","display_name":"Markov chain","score":0.3557843267917633},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.3444458246231079},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.2935749292373657},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.27886876463890076},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.11039301753044128}],"concepts":[{"id":"https://openalex.org/C23224414","wikidata":"https://www.wikidata.org/wiki/Q176769","display_name":"Hidden Markov model","level":2,"score":0.8745709657669067},{"id":"https://openalex.org/C64939953","wikidata":"https://www.wikidata.org/wiki/Q3859882","display_name":"Hidden semi-Markov model","level":5,"score":0.7941875457763672},{"id":"https://openalex.org/C196455857","wikidata":"https://www.wikidata.org/wiki/Q5473264","display_name":"Forward algorithm","level":5,"score":0.7360222339630127},{"id":"https://openalex.org/C196956702","wikidata":"https://www.wikidata.org/wiki/Q6795829","display_name":"Maximum-entropy Markov model","level":5,"score":0.6781983375549316},{"id":"https://openalex.org/C163836022","wikidata":"https://www.wikidata.org/wiki/Q6771326","display_name":"Markov model","level":3,"score":0.6211305260658264},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6105280518531799},{"id":"https://openalex.org/C164660894","wikidata":"https://www.wikidata.org/wiki/Q2037833","display_name":"Piecewise","level":2,"score":0.558782696723938},{"id":"https://openalex.org/C54907487","wikidata":"https://www.wikidata.org/wiki/Q7915688","display_name":"Variable-order Markov model","level":4,"score":0.5346108675003052},{"id":"https://openalex.org/C28490314","wikidata":"https://www.wikidata.org/wiki/Q189436","display_name":"Speech recognition","level":1,"score":0.5305212736129761},{"id":"https://openalex.org/C159886148","wikidata":"https://www.wikidata.org/wiki/Q176645","display_name":"Markov process","level":2,"score":0.5004293918609619},{"id":"https://openalex.org/C79772020","wikidata":"https://www.wikidata.org/wiki/Q5159264","display_name":"Conditional independence","level":2,"score":0.43523308634757996},{"id":"https://openalex.org/C35651441","wikidata":"https://www.wikidata.org/wiki/Q625303","display_name":"Independence (probability theory)","level":2,"score":0.43153178691864014},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.4249381422996521},{"id":"https://openalex.org/C35639132","wikidata":"https://www.wikidata.org/wiki/Q7452468","display_name":"Sequence labeling","level":3,"score":0.4171736240386963},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.39400625228881836},{"id":"https://openalex.org/C98763669","wikidata":"https://www.wikidata.org/wiki/Q176645","display_name":"Markov chain","level":2,"score":0.3557843267917633},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.3444458246231079},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.2935749292373657},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.27886876463890076},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.11039301753044128},{"id":"https://openalex.org/C187736073","wikidata":"https://www.wikidata.org/wiki/Q2920921","display_name":"Management","level":1,"score":0.0},{"id":"https://openalex.org/C2780451532","wikidata":"https://www.wikidata.org/wiki/Q759676","display_name":"Task (project management)","level":2,"score":0.0},{"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/C162324750","wikidata":"https://www.wikidata.org/wiki/Q8134","display_name":"Economics","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/icmlc.2015.7340952","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icmlc.2015.7340952","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2015 International Conference on Machine Learning and Cybernetics (ICMLC)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/16","display_name":"Peace, Justice and strong institutions","score":0.6299999952316284}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":17,"referenced_works":["https://openalex.org/W1486632395","https://openalex.org/W1984892136","https://openalex.org/W1985690171","https://openalex.org/W2037822914","https://openalex.org/W2076618452","https://openalex.org/W2083393647","https://openalex.org/W2096837052","https://openalex.org/W2124289339","https://openalex.org/W2125838338","https://openalex.org/W2138530627","https://openalex.org/W2144165558","https://openalex.org/W2152042469","https://openalex.org/W2171174827","https://openalex.org/W2294123268","https://openalex.org/W2408529216","https://openalex.org/W6696993675","https://openalex.org/W6714121785"],"related_works":["https://openalex.org/W2161328464","https://openalex.org/W4313547211","https://openalex.org/W2604015228","https://openalex.org/W3142992254","https://openalex.org/W2056043311","https://openalex.org/W2131524408","https://openalex.org/W2490979615","https://openalex.org/W1894861268","https://openalex.org/W2350115929","https://openalex.org/W1527620605"],"abstract_inverted_index":{"The":[0],"hidden":[1,26,53,113],"Markov":[2,27,54,114],"models":[3],"have":[4],"been":[5],"widely":[6],"used":[7],"in":[8],"speech":[9,80],"recognition":[10,81,105],"systems.":[11],"However,":[12],"the":[13,17,22,61,71,75,89,92,99,104],"conditional":[14],"independence":[15],"of":[16,24,74,82,91],"state":[18],"output":[19,23],"will":[20],"force":[21],"a":[25,31,39,49,111],"model":[28,55],"to":[29,58,87,110],"be":[30],"piecewise":[32,50],"constant":[33],"random":[34],"sequence,":[35],"which":[36],"is":[37,56],"not":[38],"good":[40],"approximation":[41],"for":[42,70],"many":[43],"real":[44,62],"processes.":[45],"In":[46],"this":[47],"paper,":[48],"linear":[51],"high-order":[52],"proposed":[57,76,93,100],"better":[59],"approximate":[60],"process.":[63],"An":[64],"expectation-maximization":[65],"based":[66],"algorithm":[67],"was":[68],"presented":[69],"parameter":[72],"estimation":[73],"model.":[77,115],"Experiments":[78],"on":[79],"Mandarin":[83],"digits":[84],"were":[85],"conducted":[86],"examine":[88],"effectiveness":[90],"method.":[94],"Experimental":[95],"results":[96],"show":[97],"that":[98],"method":[101],"can":[102],"reduce":[103],"error":[106],"rate":[107],"significantly":[108],"compared":[109],"baseline":[112]},"counts_by_year":[{"year":2016,"cited_by_count":2}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
