{"id":"https://openalex.org/W2938008045","doi":"https://doi.org/10.1109/icassp.2019.8683769","title":"Deep Hybrid Networks Based Response Selection for Multi-turn Dialogue Systems","display_name":"Deep Hybrid Networks Based Response Selection for Multi-turn Dialogue Systems","publication_year":2019,"publication_date":"2019-04-17","ids":{"openalex":"https://openalex.org/W2938008045","doi":"https://doi.org/10.1109/icassp.2019.8683769","mag":"2938008045"},"language":"en","primary_location":{"id":"doi:10.1109/icassp.2019.8683769","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icassp.2019.8683769","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":"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/A5009902333","display_name":"Xishuo Li","orcid":"https://orcid.org/0000-0001-8724-5809"},"institutions":[{"id":"https://openalex.org/I82880672","display_name":"Beihang University","ror":"https://ror.org/00wk2mp56","country_code":"CN","type":"education","lineage":["https://openalex.org/I82880672"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Xishuo Li","raw_affiliation_strings":["School of Computer Science and Engineering, Beihang University, Beijing, China"],"affiliations":[{"raw_affiliation_string":"School of Computer Science and Engineering, Beihang University, Beijing, China","institution_ids":["https://openalex.org/I82880672"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100448167","display_name":"Lijun Zhang","orcid":"https://orcid.org/0000-0002-9543-1000"},"institutions":[{"id":"https://openalex.org/I82880672","display_name":"Beihang University","ror":"https://ror.org/00wk2mp56","country_code":"CN","type":"education","lineage":["https://openalex.org/I82880672"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Lijun Zhang","raw_affiliation_strings":["School of Computer Science and Engineering, Beihang University, Beijing, China"],"affiliations":[{"raw_affiliation_string":"School of Computer Science and Engineering, Beihang University, Beijing, China","institution_ids":["https://openalex.org/I82880672"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5055420596","display_name":"Wenge Rong","orcid":"https://orcid.org/0000-0002-4229-7215"},"institutions":[{"id":"https://openalex.org/I82880672","display_name":"Beihang University","ror":"https://ror.org/00wk2mp56","country_code":"CN","type":"education","lineage":["https://openalex.org/I82880672"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Wenge Rong","raw_affiliation_strings":["School of Computer Science and Engineering, Beihang University, Beijing, China"],"affiliations":[{"raw_affiliation_string":"School of Computer Science and Engineering, Beihang University, Beijing, China","institution_ids":["https://openalex.org/I82880672"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5000056230","display_name":"Baiwen Li","orcid":"https://orcid.org/0000-0003-0815-5835"},"institutions":[{"id":"https://openalex.org/I82880672","display_name":"Beihang University","ror":"https://ror.org/00wk2mp56","country_code":"CN","type":"education","lineage":["https://openalex.org/I82880672"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Baiwen Li","raw_affiliation_strings":["School of Computer Science and Engineering, Beihang University, Beijing, China"],"affiliations":[{"raw_affiliation_string":"School of Computer Science and Engineering, Beihang University, Beijing, China","institution_ids":["https://openalex.org/I82880672"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5101936139","display_name":"Qi Li","orcid":"https://orcid.org/0000-0002-2825-3531"},"institutions":[{"id":"https://openalex.org/I82880672","display_name":"Beihang University","ror":"https://ror.org/00wk2mp56","country_code":"CN","type":"education","lineage":["https://openalex.org/I82880672"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Li Qi","raw_affiliation_strings":["School of Computer Science and Engineering, Beihang University, Beijing, China"],"affiliations":[{"raw_affiliation_string":"School of Computer Science and Engineering, Beihang University, Beijing, China","institution_ids":["https://openalex.org/I82880672"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":5,"corresponding_author_ids":["https://openalex.org/A5009902333"],"corresponding_institution_ids":["https://openalex.org/I82880672"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.03045267,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"17","issue":null,"first_page":"7295","last_page":"7299"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12031","display_name":"Speech and dialogue systems","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/T12031","display_name":"Speech and dialogue systems","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/T10028","display_name":"Topic Modeling","score":0.9968000054359436,"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":0.977400004863739,"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/computer-science","display_name":"Computer science","score":0.8225501775741577},{"id":"https://openalex.org/keywords/utterance","display_name":"Utterance","score":0.7746399641036987},{"id":"https://openalex.org/keywords/coherence","display_name":"Coherence (philosophical gambling strategy)","score":0.6535599827766418},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6010466814041138},{"id":"https://openalex.org/keywords/selection","display_name":"Selection (genetic algorithm)","score":0.5925742387771606},{"id":"https://openalex.org/keywords/context","display_name":"Context (archaeology)","score":0.5620924830436707},{"id":"https://openalex.org/keywords/matching","display_name":"Matching (statistics)","score":0.5604488253593445},{"id":"https://openalex.org/keywords/conversation","display_name":"Conversation","score":0.5561613440513611},{"id":"https://openalex.org/keywords/filter","display_name":"Filter (signal processing)","score":0.5129491686820984},{"id":"https://openalex.org/keywords/extractor","display_name":"Extractor","score":0.4327279031276703},{"id":"https://openalex.org/keywords/feature-selection","display_name":"Feature selection","score":0.4269477427005768},{"id":"https://openalex.org/keywords/speech-recognition","display_name":"Speech recognition","score":0.35335278511047363},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.32584434747695923},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.0840957760810852}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8225501775741577},{"id":"https://openalex.org/C2775852435","wikidata":"https://www.wikidata.org/wiki/Q258403","display_name":"Utterance","level":2,"score":0.7746399641036987},{"id":"https://openalex.org/C2781181686","wikidata":"https://www.wikidata.org/wiki/Q4226068","display_name":"Coherence (philosophical gambling strategy)","level":2,"score":0.6535599827766418},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6010466814041138},{"id":"https://openalex.org/C81917197","wikidata":"https://www.wikidata.org/wiki/Q628760","display_name":"Selection (genetic algorithm)","level":2,"score":0.5925742387771606},{"id":"https://openalex.org/C2779343474","wikidata":"https://www.wikidata.org/wiki/Q3109175","display_name":"Context (archaeology)","level":2,"score":0.5620924830436707},{"id":"https://openalex.org/C165064840","wikidata":"https://www.wikidata.org/wiki/Q1321061","display_name":"Matching (statistics)","level":2,"score":0.5604488253593445},{"id":"https://openalex.org/C2777200299","wikidata":"https://www.wikidata.org/wiki/Q52943","display_name":"Conversation","level":2,"score":0.5561613440513611},{"id":"https://openalex.org/C106131492","wikidata":"https://www.wikidata.org/wiki/Q3072260","display_name":"Filter (signal processing)","level":2,"score":0.5129491686820984},{"id":"https://openalex.org/C117978034","wikidata":"https://www.wikidata.org/wiki/Q5422192","display_name":"Extractor","level":2,"score":0.4327279031276703},{"id":"https://openalex.org/C148483581","wikidata":"https://www.wikidata.org/wiki/Q446488","display_name":"Feature selection","level":2,"score":0.4269477427005768},{"id":"https://openalex.org/C28490314","wikidata":"https://www.wikidata.org/wiki/Q189436","display_name":"Speech recognition","level":1,"score":0.35335278511047363},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.32584434747695923},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.0840957760810852},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","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/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","level":0,"score":0.0},{"id":"https://openalex.org/C62520636","wikidata":"https://www.wikidata.org/wiki/Q944","display_name":"Quantum mechanics","level":1,"score":0.0},{"id":"https://openalex.org/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","level":1,"score":0.0},{"id":"https://openalex.org/C21880701","wikidata":"https://www.wikidata.org/wiki/Q2144042","display_name":"Process engineering","level":1,"score":0.0},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.0},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"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":1,"locations":[{"id":"doi:10.1109/icassp.2019.8683769","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icassp.2019.8683769","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":[{"id":"https://openalex.org/F4320326242","display_name":"Nanfang Hospital","ror":"https://ror.org/01eq10738"},{"id":"https://openalex.org/F4320335125","display_name":"RIKEN","ror":"https://ror.org/01sjwvz98"}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":45,"referenced_works":["https://openalex.org/W10957333","https://openalex.org/W295828404","https://openalex.org/W319421170","https://openalex.org/W1522301498","https://openalex.org/W1533861849","https://openalex.org/W1836465849","https://openalex.org/W2153579005","https://openalex.org/W2173361515","https://openalex.org/W2338325072","https://openalex.org/W2339852062","https://openalex.org/W2402144811","https://openalex.org/W2521114121","https://openalex.org/W2561368124","https://openalex.org/W2605443677","https://openalex.org/W2949117887","https://openalex.org/W2953384591","https://openalex.org/W2962838727","https://openalex.org/W2962854379","https://openalex.org/W2962883855","https://openalex.org/W2963035145","https://openalex.org/W2963206148","https://openalex.org/W2963446712","https://openalex.org/W2963542836","https://openalex.org/W2963797754","https://openalex.org/W2963977677","https://openalex.org/W2964121744","https://openalex.org/W4294170691","https://openalex.org/W4295253143","https://openalex.org/W4300125564","https://openalex.org/W6600426076","https://openalex.org/W6610549151","https://openalex.org/W6623987585","https://openalex.org/W6631190155","https://openalex.org/W6631943919","https://openalex.org/W6638667902","https://openalex.org/W6640842352","https://openalex.org/W6682691769","https://openalex.org/W6685536428","https://openalex.org/W6688979741","https://openalex.org/W6703908282","https://openalex.org/W6704493726","https://openalex.org/W6713134421","https://openalex.org/W6727329663","https://openalex.org/W6745406935","https://openalex.org/W6751097180"],"related_works":["https://openalex.org/W1968552888","https://openalex.org/W2374116601","https://openalex.org/W3093134843","https://openalex.org/W2772323916","https://openalex.org/W1511346092","https://openalex.org/W1527532029","https://openalex.org/W2529301793","https://openalex.org/W2378167147","https://openalex.org/W3210777354","https://openalex.org/W3133700904"],"abstract_inverted_index":{"Proper":[0],"response":[1,41,62],"selection":[2],"is":[3],"an":[4],"important":[5],"challenge":[6],"for":[7,40],"a":[8,48,81,86,93],"meaningful":[9],"multi-turn":[10],"dialogue.":[11],"To":[12],"this":[13,44,98],"end,":[14],"not":[15],"only":[16],"the":[17,20,25,38,61,104,124],"coherence":[18],"among":[19],"whole":[21,105],"dialogue":[22],"but":[23],"also":[24],"interaction":[26],"between":[27],"utterance":[28,65],"in":[29],"adjacent":[30],"turns":[31],"need":[32],"to":[33,53,89],"be":[34,90,108],"properly":[35],"employed":[36],"as":[37,80],"context":[39],"selection.":[42],"In":[43],"paper,":[45],"we":[46,59],"propose":[47],"deep":[49,76],"hybrid":[50],"network":[51],"(DHN)":[52],"distill":[54],"such":[55],"contextual":[56,101],"information.":[57],"First,":[58],"match":[60],"with":[63,70],"each":[64],"and":[66,84,111],"filter":[67],"internal":[68],"noises":[69],"recurrent":[71],"neural":[72],"networks.":[73],"Second,":[74],"several":[75],"convolutional":[77],"blocks":[78],"perform":[79],"feature":[82],"extractor":[83],"output":[85],"matching":[87,95],"vector":[88],"fused":[91],"into":[92],"final":[94],"score.":[96],"During":[97],"period,":[99],"complex":[100],"information":[102],"across":[103],"conversation":[106],"can":[107],"thoroughly":[109],"blended":[110],"captured.":[112],"The":[113],"empirical":[114],"study":[115],"on":[116],"two":[117],"commonly":[118],"used":[119],"public":[120],"datasets":[121],"has":[122],"shown":[123],"proposed":[125],"model's":[126],"potential.":[127]},"counts_by_year":[],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}