{"id":"https://openalex.org/W2898922131","doi":"https://doi.org/10.1109/icassp.2019.8682728","title":"Neural CRF Transducers for Sequence Labeling","display_name":"Neural CRF Transducers for Sequence Labeling","publication_year":2019,"publication_date":"2019-04-16","ids":{"openalex":"https://openalex.org/W2898922131","doi":"https://doi.org/10.1109/icassp.2019.8682728","mag":"2898922131"},"language":"en","primary_location":{"id":"doi:10.1109/icassp.2019.8682728","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icassp.2019.8682728","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"ICASSP 2019 - 2019 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)","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/A5048675276","display_name":"Kai Hu","orcid":"https://orcid.org/0000-0001-7181-9935"},"institutions":[{"id":"https://openalex.org/I99065089","display_name":"Tsinghua University","ror":"https://ror.org/03cve4549","country_code":"CN","type":"education","lineage":["https://openalex.org/I99065089"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Kai Hu","raw_affiliation_strings":["Speech Processing and Machine Intelligence (SPMI) Lab, Tsinghua University, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Speech Processing and Machine Intelligence (SPMI) Lab, Tsinghua University, China","institution_ids":["https://openalex.org/I99065089"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5010173604","display_name":"Zhijian Ou","orcid":"https://orcid.org/0000-0002-9018-5074"},"institutions":[{"id":"https://openalex.org/I99065089","display_name":"Tsinghua University","ror":"https://ror.org/03cve4549","country_code":"CN","type":"education","lineage":["https://openalex.org/I99065089"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zhijian Ou","raw_affiliation_strings":["Speech Processing and Machine Intelligence (SPMI) Lab, Tsinghua University, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Speech Processing and Machine Intelligence (SPMI) Lab, Tsinghua University, China","institution_ids":["https://openalex.org/I99065089"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5091586702","display_name":"Min Hu","orcid":"https://orcid.org/0000-0003-2122-0240"},"institutions":[{"id":"https://openalex.org/I180662265","display_name":"China Mobile (China)","ror":"https://ror.org/05gftfe97","country_code":"CN","type":"company","lineage":["https://openalex.org/I180662265"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Min Hu","raw_affiliation_strings":["China Mobile Research Institute"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"China Mobile Research Institute","institution_ids":["https://openalex.org/I180662265"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5079750750","display_name":"Junlan Feng","orcid":"https://orcid.org/0000-0001-5292-2945"},"institutions":[{"id":"https://openalex.org/I180662265","display_name":"China Mobile (China)","ror":"https://ror.org/05gftfe97","country_code":"CN","type":"company","lineage":["https://openalex.org/I180662265"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Junlan Feng","raw_affiliation_strings":["China Mobile Research Institute"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"China Mobile Research Institute","institution_ids":["https://openalex.org/I180662265"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":12,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"2997","last_page":"3001"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10320","display_name":"Neural Networks and Applications","score":0.998199999332428,"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/T10320","display_name":"Neural Networks and Applications","score":0.998199999332428,"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/T14339","display_name":"Image Processing and 3D Reconstruction","score":0.9948999881744385,"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"}},{"id":"https://openalex.org/T11309","display_name":"Music and Audio Processing","score":0.9927999973297119,"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/crfs","display_name":"CRFS","score":0.9869146347045898},{"id":"https://openalex.org/keywords/conditional-random-field","display_name":"Conditional random field","score":0.888087272644043},{"id":"https://openalex.org/keywords/chunking","display_name":"Chunking (psychology)","score":0.8089147806167603},{"id":"https://openalex.org/keywords/sequence-labeling","display_name":"Sequence labeling","score":0.7966912984848022},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7306396961212158},{"id":"https://openalex.org/keywords/sequence","display_name":"Sequence (biology)","score":0.536831796169281},{"id":"https://openalex.org/keywords/recurrent-neural-network","display_name":"Recurrent neural network","score":0.5311967730522156},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5204577445983887},{"id":"https://openalex.org/keywords/speech-recognition","display_name":"Speech recognition","score":0.4762033224105835},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.4671366214752197},{"id":"https://openalex.org/keywords/transducer","display_name":"Transducer","score":0.46679526567459106},{"id":"https://openalex.org/keywords/node","display_name":"Node (physics)","score":0.41458380222320557},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.322865754365921},{"id":"https://openalex.org/keywords/acoustics","display_name":"Acoustics","score":0.10037490725517273},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.09934297204017639}],"concepts":[{"id":"https://openalex.org/C2775953691","wikidata":"https://www.wikidata.org/wiki/Q5013874","display_name":"CRFS","level":3,"score":0.9869146347045898},{"id":"https://openalex.org/C152565575","wikidata":"https://www.wikidata.org/wiki/Q1124538","display_name":"Conditional random field","level":2,"score":0.888087272644043},{"id":"https://openalex.org/C203357204","wikidata":"https://www.wikidata.org/wiki/Q1089605","display_name":"Chunking (psychology)","level":2,"score":0.8089147806167603},{"id":"https://openalex.org/C35639132","wikidata":"https://www.wikidata.org/wiki/Q7452468","display_name":"Sequence labeling","level":3,"score":0.7966912984848022},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7306396961212158},{"id":"https://openalex.org/C2778112365","wikidata":"https://www.wikidata.org/wiki/Q3511065","display_name":"Sequence (biology)","level":2,"score":0.536831796169281},{"id":"https://openalex.org/C147168706","wikidata":"https://www.wikidata.org/wiki/Q1457734","display_name":"Recurrent neural network","level":3,"score":0.5311967730522156},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5204577445983887},{"id":"https://openalex.org/C28490314","wikidata":"https://www.wikidata.org/wiki/Q189436","display_name":"Speech recognition","level":1,"score":0.4762033224105835},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.4671366214752197},{"id":"https://openalex.org/C56318395","wikidata":"https://www.wikidata.org/wiki/Q215928","display_name":"Transducer","level":2,"score":0.46679526567459106},{"id":"https://openalex.org/C62611344","wikidata":"https://www.wikidata.org/wiki/Q1062658","display_name":"Node (physics)","level":2,"score":0.41458380222320557},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.322865754365921},{"id":"https://openalex.org/C24890656","wikidata":"https://www.wikidata.org/wiki/Q82811","display_name":"Acoustics","level":1,"score":0.10037490725517273},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.09934297204017639},{"id":"https://openalex.org/C201995342","wikidata":"https://www.wikidata.org/wiki/Q682496","display_name":"Systems engineering","level":1,"score":0.0},{"id":"https://openalex.org/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","level":0,"score":0.0},{"id":"https://openalex.org/C54355233","wikidata":"https://www.wikidata.org/wiki/Q7162","display_name":"Genetics","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},{"id":"https://openalex.org/C2780451532","wikidata":"https://www.wikidata.org/wiki/Q759676","display_name":"Task (project management)","level":2,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/icassp.2019.8682728","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icassp.2019.8682728","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"ICASSP 2019 - 2019 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)","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":56,"referenced_works":["https://openalex.org/W648786980","https://openalex.org/W1515847863","https://openalex.org/W1828163288","https://openalex.org/W1899794420","https://openalex.org/W1940872118","https://openalex.org/W2027442454","https://openalex.org/W2101609803","https://openalex.org/W2104917081","https://openalex.org/W2117497855","https://openalex.org/W2119035792","https://openalex.org/W2120844411","https://openalex.org/W2126131681","https://openalex.org/W2133564696","https://openalex.org/W2137871902","https://openalex.org/W2147880316","https://openalex.org/W2157171712","https://openalex.org/W2158188757","https://openalex.org/W2158899491","https://openalex.org/W2226111737","https://openalex.org/W2250539671","https://openalex.org/W2251559320","https://openalex.org/W2296283641","https://openalex.org/W2516255829","https://openalex.org/W2556468274","https://openalex.org/W2604986524","https://openalex.org/W2756381707","https://openalex.org/W2785442381","https://openalex.org/W2808144808","https://openalex.org/W2950938254","https://openalex.org/W2952230511","https://openalex.org/W2962676330","https://openalex.org/W2962739339","https://openalex.org/W2962791537","https://openalex.org/W2962902328","https://openalex.org/W2963208801","https://openalex.org/W2963369167","https://openalex.org/W2963563735","https://openalex.org/W2963572611","https://openalex.org/W2963620441","https://openalex.org/W2963625095","https://openalex.org/W2963808856","https://openalex.org/W2964205912","https://openalex.org/W2964308564","https://openalex.org/W4293541669","https://openalex.org/W6621543089","https://openalex.org/W6638749077","https://openalex.org/W6640362995","https://openalex.org/W6678016260","https://openalex.org/W6678583454","https://openalex.org/W6679434410","https://openalex.org/W6682082992","https://openalex.org/W6683226453","https://openalex.org/W6683738474","https://openalex.org/W6694738858","https://openalex.org/W6736175030","https://openalex.org/W6748381658"],"related_works":["https://openalex.org/W2798423868","https://openalex.org/W2962906565","https://openalex.org/W3015678144","https://openalex.org/W2076440176","https://openalex.org/W2061027419","https://openalex.org/W2140585957","https://openalex.org/W1675450783","https://openalex.org/W2387017899","https://openalex.org/W189110383","https://openalex.org/W2404235285"],"abstract_inverted_index":{"Conditional":[0],"random":[1],"fields":[2],"(CRFs)":[3],"have":[4],"been":[5],"shown":[6],"to":[7,15,25],"be":[8],"one":[9,52],"of":[10,49],"the":[11,27,36,58,98],"most":[12],"successful":[13],"approaches":[14],"sequence":[16,68],"labeling.":[17],"Various":[18],"linear-chain":[19,37,91],"neural":[20],"CRFs":[21],"(NCRFs)":[22],"are":[23,71],"developed":[24],"implement":[26],"non-linear":[28],"node":[29],"potentials":[30],"in":[31],"CRFs,":[32],"but":[33],"still":[34],"keeping":[35],"hidden":[38],"structure.":[39],"In":[40],"this":[41],"paper,":[42],"we":[43],"propose":[44],"NCRF":[45,85],"transducers,":[46],"which":[47],"consists":[48],"two":[50],"RNNs,":[51],"extracting":[53],"features":[54],"from":[55],"observations":[56],"and":[57,77,93,101],"other":[59],"capturing":[60],"(theoretically":[61],"infinite)":[62],"long-range":[63],"dependencies":[64],"between":[65],"labels.":[66],"Different":[67],"labeling":[69],"methods":[70],"evaluated":[72],"over":[73,90],"POS":[74],"tagging,":[75],"chunking":[76],"NER":[78],"(English,":[79],"Dutch).":[80],"Experiment":[81],"results":[82],"show":[83],"that":[84],"transducers":[86,95],"achieve":[87],"consistent":[88],"improvements":[89],"NCRFs":[92],"RNN":[94],"across":[96],"all":[97],"four":[99],"tasks,":[100],"can":[102],"improve":[103],"state-of-the-art":[104],"results.":[105]},"counts_by_year":[{"year":2024,"cited_by_count":3},{"year":2022,"cited_by_count":1},{"year":2021,"cited_by_count":4},{"year":2020,"cited_by_count":2},{"year":2018,"cited_by_count":2}],"updated_date":"2026-07-14T23:27:15.235271","created_date":"2025-10-10T00:00:00"}