{"id":"https://openalex.org/W2964140243","doi":"https://doi.org/10.18653/v1/w16-5907","title":"Unsupervised Neural Hidden Markov Models","display_name":"Unsupervised Neural Hidden Markov Models","publication_year":2016,"publication_date":"2016-01-01","ids":{"openalex":"https://openalex.org/W2964140243","doi":"https://doi.org/10.18653/v1/w16-5907","mag":"2964140243"},"language":"en","primary_location":{"id":"doi:10.18653/v1/w16-5907","is_oa":true,"landing_page_url":"https://doi.org/10.18653/v1/w16-5907","pdf_url":"https://www.aclweb.org/anthology/W16-5907.pdf","source":null,"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the Workshop on Structured Prediction for NLP","raw_type":"proceedings-article"},"type":"conference-paper","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://www.aclweb.org/anthology/W16-5907.pdf","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5108264882","display_name":"Ke Tran","orcid":null},"institutions":[{"id":"https://openalex.org/I887064364","display_name":"University of Amsterdam","ror":"https://ror.org/04dkp9463","country_code":"NL","type":"education","lineage":["https://openalex.org/I887064364"]}],"countries":["NL"],"is_corresponding":false,"raw_author_name":"Ke M. Tran","raw_affiliation_strings":["Informatics Institute, University of Amsterdam"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Informatics Institute, University of Amsterdam","institution_ids":["https://openalex.org/I887064364"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5041302228","display_name":"Yonatan Bisk","orcid":null},"institutions":[{"id":"https://openalex.org/I1174212","display_name":"University of Southern California","ror":"https://ror.org/03taz7m60","country_code":"US","type":"education","lineage":["https://openalex.org/I1174212"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Yonatan Bisk","raw_affiliation_strings":["Information Sciences Institute, University of Southern California"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Information Sciences Institute, University of Southern California","institution_ids":["https://openalex.org/I1174212"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5103024730","display_name":"Ashish Vaswani","orcid":"https://orcid.org/0000-0002-7794-2085"},"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":"Ashish Vaswani","raw_affiliation_strings":["Google Brain, Mountain View"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Google Brain, Mountain View","institution_ids":["https://openalex.org/I1291425158"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5005020376","display_name":"Daniel Marcu","orcid":null},"institutions":[{"id":"https://openalex.org/I1174212","display_name":"University of Southern California","ror":"https://ror.org/03taz7m60","country_code":"US","type":"education","lineage":["https://openalex.org/I1174212"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Daniel Marcu","raw_affiliation_strings":["Information Sciences Institute, University of Southern California"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Information Sciences Institute, University of Southern California","institution_ids":["https://openalex.org/I1174212"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5106821597","display_name":"Kevin Knight","orcid":"https://orcid.org/0000-0001-9117-1718"},"institutions":[{"id":"https://openalex.org/I1174212","display_name":"University of Southern California","ror":"https://ror.org/03taz7m60","country_code":"US","type":"education","lineage":["https://openalex.org/I1174212"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Kevin Knight","raw_affiliation_strings":["Information Sciences Institute, University of Southern California"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Information Sciences Institute, University of Southern California","institution_ids":["https://openalex.org/I1174212"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":3,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":true,"cited_by_count":54,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"63","last_page":"71"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10028","display_name":"Topic Modeling","score":0.9998000264167786,"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/T10028","display_name":"Topic Modeling","score":0.9998000264167786,"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/T10181","display_name":"Natural Language Processing Techniques","score":0.9997000098228455,"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/T11714","display_name":"Multimodal Machine Learning Applications","score":0.9987000226974487,"subfield":{"id":"https://openalex.org/subfields/1707","display_name":"Computer Vision and Pattern Recognition"},"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":0.8482984304428101},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7898479104042053},{"id":"https://openalex.org/keywords/generative-grammar","display_name":"Generative grammar","score":0.629315972328186},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6241740584373474},{"id":"https://openalex.org/keywords/context","display_name":"Context (archaeology)","score":0.5682085156440735},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.565383791923523},{"id":"https://openalex.org/keywords/unsupervised-learning","display_name":"Unsupervised learning","score":0.545009970664978},{"id":"https://openalex.org/keywords/markov-model","display_name":"Markov model","score":0.5315009951591492},{"id":"https://openalex.org/keywords/generative-model","display_name":"Generative model","score":0.5020432472229004},{"id":"https://openalex.org/keywords/maximum-entropy-markov-model","display_name":"Maximum-entropy Markov model","score":0.478166401386261},{"id":"https://openalex.org/keywords/context-model","display_name":"Context model","score":0.46741795539855957},{"id":"https://openalex.org/keywords/markov-process","display_name":"Markov process","score":0.4546511471271515},{"id":"https://openalex.org/keywords/hidden-semi-markov-model","display_name":"Hidden semi-Markov model","score":0.42459046840667725},{"id":"https://openalex.org/keywords/markov-chain","display_name":"Markov chain","score":0.3796824812889099},{"id":"https://openalex.org/keywords/variable-order-markov-model","display_name":"Variable-order Markov model","score":0.3078347146511078},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.09121203422546387},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.046144336462020874}],"concepts":[{"id":"https://openalex.org/C23224414","wikidata":"https://www.wikidata.org/wiki/Q176769","display_name":"Hidden Markov model","level":2,"score":0.8482984304428101},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7898479104042053},{"id":"https://openalex.org/C39890363","wikidata":"https://www.wikidata.org/wiki/Q36108","display_name":"Generative grammar","level":2,"score":0.629315972328186},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6241740584373474},{"id":"https://openalex.org/C2779343474","wikidata":"https://www.wikidata.org/wiki/Q3109175","display_name":"Context (archaeology)","level":2,"score":0.5682085156440735},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.565383791923523},{"id":"https://openalex.org/C8038995","wikidata":"https://www.wikidata.org/wiki/Q1152135","display_name":"Unsupervised learning","level":2,"score":0.545009970664978},{"id":"https://openalex.org/C163836022","wikidata":"https://www.wikidata.org/wiki/Q6771326","display_name":"Markov model","level":3,"score":0.5315009951591492},{"id":"https://openalex.org/C167966045","wikidata":"https://www.wikidata.org/wiki/Q5532625","display_name":"Generative model","level":3,"score":0.5020432472229004},{"id":"https://openalex.org/C196956702","wikidata":"https://www.wikidata.org/wiki/Q6795829","display_name":"Maximum-entropy Markov model","level":5,"score":0.478166401386261},{"id":"https://openalex.org/C183322885","wikidata":"https://www.wikidata.org/wiki/Q17007702","display_name":"Context model","level":3,"score":0.46741795539855957},{"id":"https://openalex.org/C159886148","wikidata":"https://www.wikidata.org/wiki/Q176645","display_name":"Markov process","level":2,"score":0.4546511471271515},{"id":"https://openalex.org/C64939953","wikidata":"https://www.wikidata.org/wiki/Q3859882","display_name":"Hidden semi-Markov model","level":5,"score":0.42459046840667725},{"id":"https://openalex.org/C98763669","wikidata":"https://www.wikidata.org/wiki/Q176645","display_name":"Markov chain","level":2,"score":0.3796824812889099},{"id":"https://openalex.org/C54907487","wikidata":"https://www.wikidata.org/wiki/Q7915688","display_name":"Variable-order Markov model","level":4,"score":0.3078347146511078},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.09121203422546387},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.046144336462020874},{"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/C151730666","wikidata":"https://www.wikidata.org/wiki/Q7205","display_name":"Paleontology","level":1,"score":0.0}],"mesh":[],"locations_count":3,"locations":[{"id":"doi:10.18653/v1/w16-5907","is_oa":true,"landing_page_url":"https://doi.org/10.18653/v1/w16-5907","pdf_url":"https://www.aclweb.org/anthology/W16-5907.pdf","source":null,"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the Workshop on Structured Prediction for NLP","raw_type":"proceedings-article"},{"id":"pmh:oai:dare.uva.nl:openaire_cris_publications/a0eeb5b4-a932-47eb-a2f3-6ae5624a62c9","is_oa":true,"landing_page_url":"https://handle.uba.uva.nl/personal/pure/en/publications/unsupervised-neural-hidden-markov-models(a0eeb5b4-a932-47eb-a2f3-6ae5624a62c9).html","pdf_url":null,"source":{"id":"https://openalex.org/S4306400088","display_name":"UvA-DARE (University of Amsterdam)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I887064364","host_organization_name":"University of Amsterdam","host_organization_lineage":["https://openalex.org/I887064364"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Tran, K, Bisk, Y, Vaswani, A, Marcu, D & Knight, K 2016, Unsupervised Neural Hidden Markov Models. in K-W Chang, M-W Chang, A Rush & V Srikumar (eds), EMNLP 2016 : Conference on Empirical Methods in Natural Language Processing : proceedings of the Workshop on Structured Prediction for Natural Language Processing : November 5, 2016, Austin, Texas, USA. Stroudsburg, PA, pp. 63-71, Empirical Methods in Natural Language Processing, 2/11/16. https://doi.org/10.18653/v1/W16-5907","raw_type":"info:eu-repo/semantics/conferenceObject"},{"id":"pmh:uvapub:oai:dare.uva.nl:publications/a0eeb5b4-a932-47eb-a2f3-6ae5624a62c9","is_oa":true,"landing_page_url":"https://dare.uva.nl/personal/pure/en/publications/unsupervised-neural-hidden-markov-models(a0eeb5b4-a932-47eb-a2f3-6ae5624a62c9).html","pdf_url":"https://dare.uva.nl/personal/pure/en/publications/unsupervised-neural-hidden-markov-models(a0eeb5b4-a932-47eb-a2f3-6ae5624a62c9).html","source":{"id":"https://openalex.org/S4306401843","display_name":"Data Archiving and Networked Services (DANS)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I1322597698","host_organization_name":"Royal Netherlands Academy of Arts and Sciences","host_organization_lineage":["https://openalex.org/I1322597698"],"host_organization_lineage_names":[],"type":"repository"},"license":"other-oa","license_id":"https://openalex.org/licenses/other-oa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"EMNLP 2016 : Conference on Empirical Methods in Natural Language Processing : proceedings of the Workshop on Structured Prediction for Natural Language Processing: November 5, 2016, Austin, Texas, USA, 63 - 71","raw_type":"info:eu-repo/semantics/conferencepaper"}],"best_oa_location":{"id":"doi:10.18653/v1/w16-5907","is_oa":true,"landing_page_url":"https://doi.org/10.18653/v1/w16-5907","pdf_url":"https://www.aclweb.org/anthology/W16-5907.pdf","source":null,"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the Workshop on Structured Prediction for NLP","raw_type":"proceedings-article"},"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G5385673730","display_name":null,"funder_award_id":"W911NF-15-1-","funder_id":"https://openalex.org/F4320338281","funder_display_name":"Army Research Office"},{"id":"https://openalex.org/G7452299184","display_name":null,"funder_award_id":"W911NF","funder_id":"https://openalex.org/F4320338281","funder_display_name":"Army Research Office"},{"id":"https://openalex.org/G8092615179","display_name":null,"funder_award_id":"HR0011-15-C-0115","funder_id":"https://openalex.org/F4320332180","funder_display_name":"Defense Advanced Research Projects Agency"}],"funders":[{"id":"https://openalex.org/F4320332180","display_name":"Defense Advanced Research Projects Agency","ror":"https://ror.org/02caytj08"},{"id":"https://openalex.org/F4320332815","display_name":"Advanced Research Projects Agency","ror":"https://ror.org/02caytj08"},{"id":"https://openalex.org/F4320338281","display_name":"Army Research Office","ror":"https://ror.org/05epdh915"}],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W2964140243.pdf","grobid_xml":"https://content.openalex.org/works/W2964140243.grobid-xml"},"referenced_works_count":40,"referenced_works":["https://openalex.org/W581956982","https://openalex.org/W932413789","https://openalex.org/W1522301498","https://openalex.org/W1570013475","https://openalex.org/W1801581093","https://openalex.org/W1826234144","https://openalex.org/W1831478036","https://openalex.org/W1902237438","https://openalex.org/W1909733559","https://openalex.org/W1938755728","https://openalex.org/W1959608418","https://openalex.org/W1987937363","https://openalex.org/W2049633694","https://openalex.org/W2064675550","https://openalex.org/W2093647425","https://openalex.org/W2095705004","https://openalex.org/W2104441213","https://openalex.org/W2108622839","https://openalex.org/W2109389484","https://openalex.org/W2110799598","https://openalex.org/W2120861206","https://openalex.org/W2121227244","https://openalex.org/W2142523187","https://openalex.org/W2148099973","https://openalex.org/W2152790380","https://openalex.org/W2155042384","https://openalex.org/W2164119735","https://openalex.org/W2250765246","https://openalex.org/W2251652451","https://openalex.org/W2252238553","https://openalex.org/W2259472270","https://openalex.org/W2464234964","https://openalex.org/W2470595162","https://openalex.org/W2951559648","https://openalex.org/W2951595529","https://openalex.org/W2962695963","https://openalex.org/W2963077125","https://openalex.org/W2963560804","https://openalex.org/W2964121744","https://openalex.org/W2964325005"],"related_works":["https://openalex.org/W2382132287","https://openalex.org/W1615861041","https://openalex.org/W2379333870","https://openalex.org/W3113307220","https://openalex.org/W2161328464","https://openalex.org/W1972679863","https://openalex.org/W1542903750","https://openalex.org/W2118728396","https://openalex.org/W1917205115","https://openalex.org/W2361306765"],"abstract_inverted_index":{"In":[0],"this":[1],"work,":[2],"we":[3],"present":[4],"the":[5,32],"first":[6],"results":[7],"for":[8],"neuralizing":[9],"an":[10],"Unsupervised":[11],"Hidden":[12],"Markov":[13],"Model.":[14],"We":[15],"evaluate":[16],"our":[17],"approach":[18,23],"on":[19],"tag":[20],"induction.":[21],"Our":[22],"outperforms":[24],"existing":[25],"generative":[26],"models":[27],"and":[28],"is":[29],"competitive":[30],"with":[31,35],"state-of-the-art":[33],"though":[34],"a":[36],"simpler":[37],"model":[38],"easily":[39],"extended":[40],"to":[41],"include":[42],"additional":[43],"context.":[44]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":1},{"year":2023,"cited_by_count":5},{"year":2022,"cited_by_count":11},{"year":2021,"cited_by_count":14},{"year":2020,"cited_by_count":4},{"year":2019,"cited_by_count":10},{"year":2018,"cited_by_count":5},{"year":2017,"cited_by_count":3}],"updated_date":"2026-07-14T23:27:15.235271","created_date":"2025-10-10T00:00:00"}