{"id":"https://openalex.org/W2097432293","doi":"https://doi.org/10.1109/icdar.2015.7333863","title":"Label transition and selection pruning and automatic decoding parameter optimization for time-synchronous Viterbi decoding","display_name":"Label transition and selection pruning and automatic decoding parameter optimization for time-synchronous Viterbi decoding","publication_year":2015,"publication_date":"2015-08-01","ids":{"openalex":"https://openalex.org/W2097432293","doi":"https://doi.org/10.1109/icdar.2015.7333863","mag":"2097432293"},"language":"en","primary_location":{"id":"doi:10.1109/icdar.2015.7333863","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icdar.2015.7333863","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2015 13th International Conference on Document Analysis and Recognition (ICDAR)","raw_type":"proceedings-article"},"type":"conference-paper","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/A5102171465","display_name":"Yasuhisa Fujii","orcid":null},"institutions":[{"id":"https://openalex.org/I1291425158","display_name":"Google (United States)","ror":"https://ror.org/00njsd438","country_code":"US","type":"company","lineage":["https://openalex.org/I1291425158","https://openalex.org/I4210128969"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Yasuhisa Fujii","raw_affiliation_strings":["Google Research, Mountain View, CA","Google Research, Mountain View, CA 94043, USA#TAB#"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Google Research, Mountain View, CA","institution_ids":["https://openalex.org/I1291425158"]},{"raw_affiliation_string":"Google Research, Mountain View, CA 94043, USA#TAB#","institution_ids":["https://openalex.org/I1291425158"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5048470138","display_name":"Dmitriy Genzel","orcid":null},"institutions":[{"id":"https://openalex.org/I1291425158","display_name":"Google (United States)","ror":"https://ror.org/00njsd438","country_code":"US","type":"company","lineage":["https://openalex.org/I1291425158","https://openalex.org/I4210128969"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Dmitriy Genzel","raw_affiliation_strings":["Google Research, Mountain View, CA","Google Research, Mountain View, CA 94043, USA#TAB#"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Google Research, Mountain View, CA","institution_ids":["https://openalex.org/I1291425158"]},{"raw_affiliation_string":"Google Research, Mountain View, CA 94043, USA#TAB#","institution_ids":["https://openalex.org/I1291425158"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5078560039","display_name":"Ashok C. Popat","orcid":null},"institutions":[{"id":"https://openalex.org/I1291425158","display_name":"Google (United States)","ror":"https://ror.org/00njsd438","country_code":"US","type":"company","lineage":["https://openalex.org/I1291425158","https://openalex.org/I4210128969"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Ashok C. Popat","raw_affiliation_strings":["Google Research, Mountain View, CA","Google Research, Mountain View, CA 94043, USA#TAB#"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Google Research, Mountain View, CA","institution_ids":["https://openalex.org/I1291425158"]},{"raw_affiliation_string":"Google Research, Mountain View, CA 94043, USA#TAB#","institution_ids":["https://openalex.org/I1291425158"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5021837944","display_name":"Remco Teunen","orcid":null},"institutions":[{"id":"https://openalex.org/I1291425158","display_name":"Google (United States)","ror":"https://ror.org/00njsd438","country_code":"US","type":"company","lineage":["https://openalex.org/I1291425158","https://openalex.org/I4210128969"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Remco Teunen","raw_affiliation_strings":["Google Research, Mountain View, CA","Google Research, Mountain View, CA 94043, USA#TAB#"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Google Research, Mountain View, CA","institution_ids":["https://openalex.org/I1291425158"]},{"raw_affiliation_string":"Google Research, Mountain View, CA 94043, USA#TAB#","institution_ids":["https://openalex.org/I1291425158"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I1291425158"],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":7,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"756","last_page":"760"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11269","display_name":"Algorithms and Data Compression","score":0.9994000196456909,"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/T11269","display_name":"Algorithms and Data Compression","score":0.9994000196456909,"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/T10201","display_name":"Speech Recognition and Synthesis","score":0.9945999979972839,"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/T11447","display_name":"Blind Source Separation Techniques","score":0.9937999844551086,"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":0.8302414417266846},{"id":"https://openalex.org/keywords/decoding-methods","display_name":"Decoding methods","score":0.8149338960647583},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7807557582855225},{"id":"https://openalex.org/keywords/viterbi-algorithm","display_name":"Viterbi algorithm","score":0.7437331676483154},{"id":"https://openalex.org/keywords/pruning","display_name":"Pruning","score":0.7259169816970825},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5264920592308044},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.4875878691673279},{"id":"https://openalex.org/keywords/segmentation","display_name":"Segmentation","score":0.4777754545211792},{"id":"https://openalex.org/keywords/speech-recognition","display_name":"Speech recognition","score":0.4744464159011841},{"id":"https://openalex.org/keywords/sequential-decoding","display_name":"Sequential decoding","score":0.4405202865600586},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.3882410526275635}],"concepts":[{"id":"https://openalex.org/C23224414","wikidata":"https://www.wikidata.org/wiki/Q176769","display_name":"Hidden Markov model","level":2,"score":0.8302414417266846},{"id":"https://openalex.org/C57273362","wikidata":"https://www.wikidata.org/wiki/Q576722","display_name":"Decoding methods","level":2,"score":0.8149338960647583},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7807557582855225},{"id":"https://openalex.org/C60582962","wikidata":"https://www.wikidata.org/wiki/Q83886","display_name":"Viterbi algorithm","level":3,"score":0.7437331676483154},{"id":"https://openalex.org/C108010975","wikidata":"https://www.wikidata.org/wiki/Q500094","display_name":"Pruning","level":2,"score":0.7259169816970825},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5264920592308044},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.4875878691673279},{"id":"https://openalex.org/C89600930","wikidata":"https://www.wikidata.org/wiki/Q1423946","display_name":"Segmentation","level":2,"score":0.4777754545211792},{"id":"https://openalex.org/C28490314","wikidata":"https://www.wikidata.org/wiki/Q189436","display_name":"Speech recognition","level":1,"score":0.4744464159011841},{"id":"https://openalex.org/C193969084","wikidata":"https://www.wikidata.org/wiki/Q7452500","display_name":"Sequential decoding","level":4,"score":0.4405202865600586},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.3882410526275635},{"id":"https://openalex.org/C6557445","wikidata":"https://www.wikidata.org/wiki/Q173113","display_name":"Agronomy","level":1,"score":0.0},{"id":"https://openalex.org/C157125643","wikidata":"https://www.wikidata.org/wiki/Q884707","display_name":"Block code","level":3,"score":0.0},{"id":"https://openalex.org/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/icdar.2015.7333863","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icdar.2015.7333863","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2015 13th International Conference on Document Analysis and Recognition (ICDAR)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":18,"referenced_works":["https://openalex.org/W15592790","https://openalex.org/W1553004968","https://openalex.org/W1996960689","https://openalex.org/W2001642682","https://openalex.org/W2016185147","https://openalex.org/W2105891181","https://openalex.org/W2109664771","https://openalex.org/W2129265797","https://openalex.org/W2149043292","https://openalex.org/W2149298150","https://openalex.org/W2157515255","https://openalex.org/W2168231600","https://openalex.org/W2183866593","https://openalex.org/W6600622082","https://openalex.org/W6650820226","https://openalex.org/W6676373471","https://openalex.org/W6684859321","https://openalex.org/W6686499835"],"related_works":["https://openalex.org/W2136652457","https://openalex.org/W2169849734","https://openalex.org/W2116722627","https://openalex.org/W2129150969","https://openalex.org/W2236912844","https://openalex.org/W1975869217","https://openalex.org/W2401728283","https://openalex.org/W2383829109","https://openalex.org/W2379938888","https://openalex.org/W2386035178"],"abstract_inverted_index":{"Hidden":[0],"Markov":[1],"Model":[2],"(HMM)-based":[3],"classifiers":[4,79],"have":[5,24],"been":[6,25],"successfully":[7],"used":[8],"for":[9,21,104],"sequential":[10],"labeling":[11],"problems":[12],"such":[13],"as":[14],"speech":[15],"recognition":[16,20],"and":[17],"optical":[18],"character":[19],"decades.":[22],"They":[23],"especially":[26],"successful":[27],"in":[28,42],"the":[29,32,54,89,102,115],"domains":[30],"where":[31],"segmentation":[33,46],"is":[34],"not":[35],"known":[36],"or":[37],"difficult":[38,99],"to":[39,73,82,100,113],"obtain,":[40],"since,":[41],"principle,":[43],"all":[44],"possible":[45],"points":[47],"can":[48],"be":[49],"taken":[50],"into":[51],"account.":[52],"However,":[53],"benefit":[55],"comes":[56],"with":[57,77],"a":[58,86,110,119,125],"non-negligible":[59],"computational":[60],"cost.":[61],"In":[62],"this":[63],"paper,":[64],"we":[65],"propose":[66,109],"simple":[67],"yet":[68],"effective":[69],"new":[70],"pruning":[71],"algorithms":[72],"speed":[74],"up":[75,81],"decoding":[76,93],"HMM-based":[78],"of":[80,91],"95%":[83],"relative":[84],"over":[85],"baseline.":[87],"As":[88],"number":[90],"tunable":[92],"parameters":[94,103,116],"increases,":[95],"it":[96],"becomes":[97],"more":[98],"optimize":[101],"each":[105],"configuration.":[106],"We":[107],"also":[108],"novel":[111],"technique":[112],"estimate":[114],"based":[117],"on":[118,124],"loss":[120],"value":[121],"without":[122],"relying":[123],"grid":[126],"search.":[127]},"counts_by_year":[{"year":2023,"cited_by_count":1},{"year":2018,"cited_by_count":2},{"year":2017,"cited_by_count":3},{"year":2015,"cited_by_count":1}],"updated_date":"2026-07-14T23:27:15.235271","created_date":"2025-10-10T00:00:00"}