{"id":"https://openalex.org/W3016164858","doi":"https://doi.org/10.1109/icassp40776.2020.9052929","title":"Integrating Discrete and Neural Features Via Mixed-Feature Trans-Dimensional Random Field Language Models","display_name":"Integrating Discrete and Neural Features Via Mixed-Feature Trans-Dimensional Random Field Language Models","publication_year":2020,"publication_date":"2020-04-09","ids":{"openalex":"https://openalex.org/W3016164858","doi":"https://doi.org/10.1109/icassp40776.2020.9052929","mag":"3016164858"},"language":"en","primary_location":{"id":"doi:10.1109/icassp40776.2020.9052929","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icassp40776.2020.9052929","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"ICASSP 2020 - 2020 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/A5103244807","display_name":"Silin Gao","orcid":"https://orcid.org/0000-0003-0073-578X"},"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":true,"raw_author_name":"Silin Gao","raw_affiliation_strings":["Speech Processing and Machine Intelligence (SPMI) Lab, Tsinghua University, Beijing, China"],"affiliations":[{"raw_affiliation_string":"Speech Processing and Machine Intelligence (SPMI) Lab, Tsinghua University, Beijing, 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, Beijing, China"],"affiliations":[{"raw_affiliation_string":"Speech Processing and Machine Intelligence (SPMI) Lab, Tsinghua University, Beijing, China","institution_ids":["https://openalex.org/I99065089"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101866601","display_name":"Wei Yang","orcid":"https://orcid.org/0000-0003-1266-048X"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Wei Yang","raw_affiliation_strings":["State Grid Customer Service Center"],"affiliations":[{"raw_affiliation_string":"State Grid Customer Service Center","institution_ids":[]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5109411570","display_name":"Huifang Xu","orcid":null},"institutions":[{"id":"https://openalex.org/I4392738113","display_name":"China Electric Power Research Institute","ror":"https://ror.org/05ehpzy81","country_code":null,"type":"facility","lineage":["https://openalex.org/I17442442","https://openalex.org/I4392738113"]},{"id":"https://openalex.org/I153473198","display_name":"North China Electric Power University","ror":"https://ror.org/04qr5t414","country_code":"CN","type":"education","lineage":["https://openalex.org/I153473198"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Huifang Xu","raw_affiliation_strings":["China Electric Power Research Institute"],"affiliations":[{"raw_affiliation_string":"China Electric Power Research Institute","institution_ids":["https://openalex.org/I153473198","https://openalex.org/I4392738113"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5103244807"],"corresponding_institution_ids":["https://openalex.org/I99065089"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":2,"citation_normalized_percentile":{"value":0.03578863,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":94,"max":96},"biblio":{"volume":null,"issue":null,"first_page":"6169","last_page":"6173"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10201","display_name":"Speech Recognition and Synthesis","score":0.9998999834060669,"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":0.9998999834060669,"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/T11309","display_name":"Music and Audio Processing","score":0.9987999796867371,"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/T10028","display_name":"Topic Modeling","score":0.9987000226974487,"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/feature","display_name":"Feature (linguistics)","score":0.714802622795105},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7145733833312988},{"id":"https://openalex.org/keywords/interpolation","display_name":"Interpolation (computer graphics)","score":0.6996327042579651},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.6244322061538696},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.5194951295852661},{"id":"https://openalex.org/keywords/field","display_name":"Field (mathematics)","score":0.5189142227172852},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.4899217486381531},{"id":"https://openalex.org/keywords/set","display_name":"Set (abstract data type)","score":0.48944607377052307},{"id":"https://openalex.org/keywords/speech-recognition","display_name":"Speech recognition","score":0.37947675585746765},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.1859024465084076}],"concepts":[{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.714802622795105},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7145733833312988},{"id":"https://openalex.org/C137800194","wikidata":"https://www.wikidata.org/wiki/Q11713455","display_name":"Interpolation (computer graphics)","level":3,"score":0.6996327042579651},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.6244322061538696},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.5194951295852661},{"id":"https://openalex.org/C9652623","wikidata":"https://www.wikidata.org/wiki/Q190109","display_name":"Field (mathematics)","level":2,"score":0.5189142227172852},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4899217486381531},{"id":"https://openalex.org/C177264268","wikidata":"https://www.wikidata.org/wiki/Q1514741","display_name":"Set (abstract data type)","level":2,"score":0.48944607377052307},{"id":"https://openalex.org/C28490314","wikidata":"https://www.wikidata.org/wiki/Q189436","display_name":"Speech recognition","level":1,"score":0.37947675585746765},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.1859024465084076},{"id":"https://openalex.org/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"score":0.0},{"id":"https://openalex.org/C202444582","wikidata":"https://www.wikidata.org/wiki/Q837863","display_name":"Pure mathematics","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/C104114177","wikidata":"https://www.wikidata.org/wiki/Q79782","display_name":"Motion (physics)","level":2,"score":0.0},{"id":"https://openalex.org/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/icassp40776.2020.9052929","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icassp40776.2020.9052929","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"ICASSP 2020 - 2020 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/4","score":0.6299999952316284,"display_name":"Quality Education"}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":33,"referenced_works":["https://openalex.org/W1522301498","https://openalex.org/W1632114991","https://openalex.org/W1932968309","https://openalex.org/W1970689298","https://openalex.org/W2050971845","https://openalex.org/W2080018251","https://openalex.org/W2114858359","https://openalex.org/W2130437494","https://openalex.org/W2158195707","https://openalex.org/W2167717037","https://openalex.org/W2171928131","https://openalex.org/W2251519907","https://openalex.org/W2402268235","https://openalex.org/W2516932417","https://openalex.org/W2519314406","https://openalex.org/W2521736912","https://openalex.org/W2608339501","https://openalex.org/W2611669587","https://openalex.org/W2951714314","https://openalex.org/W2952613254","https://openalex.org/W2956159074","https://openalex.org/W2962736473","https://openalex.org/W2963034893","https://openalex.org/W2963640903","https://openalex.org/W2964121744","https://openalex.org/W2964147652","https://openalex.org/W4288290348","https://openalex.org/W6631190155","https://openalex.org/W6632248436","https://openalex.org/W6713098461","https://openalex.org/W6726225612","https://openalex.org/W6726378182","https://openalex.org/W6765658108"],"related_works":["https://openalex.org/W3147584709","https://openalex.org/W2391251536","https://openalex.org/W2977677679","https://openalex.org/W2362198218","https://openalex.org/W1992327129","https://openalex.org/W1982750869","https://openalex.org/W2019521278","https://openalex.org/W1984922432","https://openalex.org/W2381986121","https://openalex.org/W4388321867"],"abstract_inverted_index":{"There":[0],"has":[1,49],"been":[2],"a":[3,34,59,80],"long":[4],"recognition":[5],"that":[6],"discrete":[7,39,66,90,132,156],"features":[8,15,69,159],"(n-gram":[9],"features)":[10],"and":[11,40,84,91,100,104,135,140,157,172,178],"neural":[12,41,68,92,136,158],"network":[13],"based":[14],"have":[16],"complementary":[17],"strengths":[18],"for":[19,111],"language":[20],"models":[21,154],"(LMs).":[22],"Improved":[23],"performance":[24,162],"can":[25],"be":[26],"obtained":[27],"by":[28],"model":[29,120],"interpolation,":[30],"which":[31],"is,":[32],"however,":[33],"sub-optimal":[35],"two-step":[36],"integration":[37],"of":[38,53,62,163],"features.":[42,63,93],"The":[43],"trans-dimensional":[44],"random":[45],"field":[46],"(TRF)":[47],"framework":[48],"the":[50,122,127,161,168],"potential":[51],"advantage":[52,87],"being":[54,142],"able":[55],"to":[56,149],"flexibly":[57],"integrate":[58],"richer":[60],"set":[61],"However,":[64],"either":[65],"or":[67],"are":[70,96],"used":[71],"alone":[72],"in":[73,88,106],"previous":[74],"TRF":[75,82,124,133,137,165],"LMs.":[76,147],"This":[77],"paper":[78],"develops":[79],"mixed-feature":[81,123,164],"LM":[83],"demonstrates":[85],"its":[86],"integrating":[89],"Various":[94],"LMs":[95,117,125,134,138,166],"trained":[97,153],"over":[98,130],"PTB":[99],"Google":[101],"one-billion-word":[102],"datasets,":[103],"evaluated":[105],"N-best":[107],"list":[108],"rescoring":[109],"experiments":[110],"speech":[112],"recognition.":[113],"Among":[114],"all":[115],"single":[116],"(i.e.":[118],"without":[119],"interpolation),":[121],"perform":[126],"best,":[128],"improving":[129],"both":[131],"alone,":[139],"also":[141],"significantly":[143],"better":[144],"than":[145],"LSTM":[146],"Compared":[148],"interpolating":[150],"two":[151],"separately":[152],"with":[155,173],"respectively,":[160],"matches":[167],"best":[169],"interpolated":[170],"model,":[171],"simplified":[174],"one-step":[175],"training":[176,180],"process":[177],"reduced":[179],"time.":[181]},"counts_by_year":[{"year":2024,"cited_by_count":2}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
