乐胖代购免代理版

{"id":"https://openalex.org/W2101662437","doi":"https://doi.org/10.1109/icassp.2006.1660235","title":"Estimating Trajectory Hmm Parameters Using Monte Carlo Em With Gibbs Sampler","display_name":"Estimating Trajectory Hmm Parameters Using Monte Carlo Em With Gibbs Sampler","publication_year":2006,"publication_date":"2006-08-03","ids":{"openalex":"https://openalex.org/W2101662437","doi":"https://doi.org/10.1109/icassp.2006.1660235","mag":"2101662437"},"language":"en","primary_location":{"is_oa":false,"landing_page_url":"https://doi.org/10.1109/icassp.2006.1660235","pdf_url":null,"source":null,"license":null,"license_id":null,"version":null,"is_accepted":false,"is_published":false},"type":"article","type_crossref":"proceedings-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/A5003420204","display_name":"Heiga Zen","orcid":"https://orcid.org/0000-0002-8959-5471"},"institutions":[{"id":"https://openalex.org/I197274945","display_name":"Nagoya Institute of Technology","ror":"https://ror.org/055yf1005","country_code":"JP","type":"education","lineage":["https://openalex.org/I197274945"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"None Heiga Zen","raw_affiliation_strings":["Nagoya Institute of Technology, Department of Computer Science and Engineering, Gokiso-cho, Showa-ku, Nagoya 466-8555 Japan. zen@ics.nitech.ac.jp"],"affiliations":[{"raw_affiliation_string":"Nagoya Institute of Technology, Department of Computer Science and Engineering, Gokiso-cho, Showa-ku, Nagoya 466-8555 Japan. zen@ics.nitech.ac.jp","institution_ids":["https://openalex.org/I197274945"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5023240652","display_name":"Yoshihiko Nankaku","orcid":null},"institutions":[{"id":"https://openalex.org/I197274945","display_name":"Nagoya Institute of Technology","ror":"https://ror.org/055yf1005","country_code":"JP","type":"education","lineage":["https://openalex.org/I197274945"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Y. Nankaku","raw_affiliation_strings":["Department of Computer Science and Engineering, Nagoya Institute of Technology#TAB#"],"affiliations":[{"raw_affiliation_string":"Department of Computer Science and Engineering, Nagoya Institute of Technology#TAB#","institution_ids":["https://openalex.org/I197274945"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5103023678","display_name":"Keiichi Tokuda","orcid":"https://orcid.org/0000-0001-6143-0133"},"institutions":[{"id":"https://openalex.org/I197274945","display_name":"Nagoya Institute of Technology","ror":"https://ror.org/055yf1005","country_code":"JP","type":"education","lineage":["https://openalex.org/I197274945"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"K. Tokuda","raw_affiliation_strings":["Department of Computer Science and Engineering, Nagoya Institute of Technology#TAB#"],"affiliations":[{"raw_affiliation_string":"Department of Computer Science and Engineering, Nagoya Institute of Technology#TAB#","institution_ids":["https://openalex.org/I197274945"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5059137996","display_name":"Tadashi Kitamura","orcid":null},"institutions":[{"id":"https://openalex.org/I197274945","display_name":"Nagoya Institute of Technology","ror":"https://ror.org/055yf1005","country_code":"JP","type":"education","lineage":["https://openalex.org/I197274945"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"T. Kitamura","raw_affiliation_strings":["Department of Computer Science and Engineering, Nagoya Institute of Technology#TAB#"],"affiliations":[{"raw_affiliation_string":"Department of Computer Science and Engineering, Nagoya Institute of Technology#TAB#","institution_ids":["https://openalex.org/I197274945"]}]}],"institution_assertions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.417,"has_fulltext":true,"fulltext_origin":"ngrams","cited_by_count":5,"citation_normalized_percentile":{"value":0.578689,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":76,"max":78},"biblio":{"volume":null,"issue":null,"first_page":null,"last_page":null},"is_retracted":false,"is_paratext":false,"primary_topic":{"id":"https://openalex.org/T10201","display_name":"Speech Recognition and Synthesis","score":0.9971,"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":0.9971,"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":0.9964,"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/T10711","display_name":"Target Tracking and Data Fusion in Sensor Networks","score":0.9924,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/gibbs-sampling","display_name":"Gibbs sampling","score":0.77318275},{"id":"https://openalex.org/keywords/independence","display_name":"Independence","score":0.5328743},{"id":"https://openalex.org/keywords/conditional-independence","display_name":"Conditional independence","score":0.4893257}],"concepts":[{"id":"https://openalex.org/C23224414","wikidata":"https://www.wikidata.org/wiki/Q176769","display_name":"Hidden Markov model","level":2,"score":0.90359956},{"id":"https://openalex.org/C158424031","wikidata":"https://www.wikidata.org/wiki/Q1191905","display_name":"Gibbs sampling","level":3,"score":0.77318275},{"id":"https://openalex.org/C13662910","wikidata":"https://www.wikidata.org/wiki/Q193139","display_name":"Trajectory","level":2,"score":0.75418305},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6074824},{"id":"https://openalex.org/C19499675","wikidata":"https://www.wikidata.org/wiki/Q232207","display_name":"Monte Carlo method","level":2,"score":0.5994499},{"id":"https://openalex.org/C35651441","wikidata":"https://www.wikidata.org/wiki/Q625303","display_name":"Independence (probability theory)","level":2,"score":0.5328743},{"id":"https://openalex.org/C79772020","wikidata":"https://www.wikidata.org/wiki/Q5159264","display_name":"Conditional independence","level":2,"score":0.4893257},{"id":"https://openalex.org/C111350023","wikidata":"https://www.wikidata.org/wiki/Q1191869","display_name":"Markov chain Monte Carlo","level":3,"score":0.4132526},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.37936446},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.3711965},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.32940522},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.32196757},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.27985638},{"id":"https://openalex.org/C107673813","wikidata":"https://www.wikidata.org/wiki/Q812534","display_name":"Bayesian probability","level":2,"score":0.09983769},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.049455673},{"id":"https://openalex.org/C1276947","wikidata":"https://www.wikidata.org/wiki/Q333","display_name":"Astronomy","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"is_oa":false,"landing_page_url":"https://doi.org/10.1109/icassp.2006.1660235","pdf_url":null,"source":null,"license":null,"license_id":null,"version":null,"is_accepted":false,"is_published":false}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/16","display_name":"Peace, justice, and strong institutions","score":0.45}],"grants":[],"datasets":[],"versions":[],"referenced_works_count":8,"referenced_works":["https://openalex.org/W1994396704","https://openalex.org/W2072634211","https://openalex.org/W2083393647","https://openalex.org/W2136652457","https://openalex.org/W2468248883","https://openalex.org/W32588098","https://openalex.org/W4245883374","https://openalex.org/W59130454"],"related_works":["https://openalex.org/W3139342328","https://openalex.org/W3125971950","https://openalex.org/W2905524938","https://openalex.org/W2622204791","https://openalex.org/W2175355783","https://openalex.org/W2116700007","https://openalex.org/W2066716418","https://openalex.org/W1580681286","https://openalex.org/W1579866848","https://openalex.org/W1546022168"],"abstract_inverted_index":{"In":[0,72],"the":[1,4,47,67,83,90,95],"present":[2],"paper,":[3],"Monte":[5],"Carlo":[6],"EM":[7,96],"(MCEM)":[8],"algorithm":[9,85],"with":[10],"a":[11,20,55,73],"Gibbs":[12],"sampler":[13],"is":[14],"applied":[15],"for":[16],"estimating":[17],"parameters":[18],"of":[19,46,61,69],"trajectory":[21,40,79],"HMM,":[22,48],"which":[23,49],"has":[24],"been":[25],"derived":[26],"from":[27],"an":[28],"HMM":[29,41],"by":[30,82,94],"imposing":[31],"explicit":[32],"relationships":[33],"between":[34],"static":[35],"and":[36,57],"dynamic":[37],"features.":[38],"The":[39],"can":[42],"alleviate":[43],"two":[44],"limitations":[45],"are":[50],"i)":[51],"constant":[52],"statistics":[53],"within":[54],"state,":[56],"ii)":[58],"conditional":[59],"independence":[60],"state":[62],"output":[63],"probabilities,":[64],"without":[65],"increasing":[66],"number":[68],"model":[70],"parameters.":[71],"speaker-dependent":[74],"continuous":[75],"speech":[76],"recognition":[77],"experiment,":[78],"HMMs":[80,92],"estimated":[81],"MCEM":[84],"achieved":[86],"significant":[87],"improvements":[88],"over":[89],"corresponding":[91],"trained":[93],"(Baum-Welch)":[97],"algorithm.":[98]},"cited_by_api_url":"https://api.openalex.org/works?filter=cites:W2101662437","counts_by_year":[{"year":2014,"cited_by_count":1}],"updated_date":"2025-01-20T17:19:40.437068","created_date":"2016-06-24"}