{"id":"https://openalex.org/W2939248538","doi":"https://doi.org/10.1109/icassp.2019.8683783","title":"Improving Layer Trajectory LSTM with Future Context Frames","display_name":"Improving Layer Trajectory LSTM with Future Context Frames","publication_year":2019,"publication_date":"2019-04-16","ids":{"openalex":"https://openalex.org/W2939248538","doi":"https://doi.org/10.1109/icassp.2019.8683783","mag":"2939248538"},"language":"en","primary_location":{"id":"doi:10.1109/icassp.2019.8683783","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icassp.2019.8683783","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/A5100365053","display_name":"Jinyu Li","orcid":"https://orcid.org/0000-0002-1089-9748"},"institutions":[{"id":"https://openalex.org/I1290206253","display_name":"Microsoft (United States)","ror":"https://ror.org/00d0nc645","country_code":"US","type":"company","lineage":["https://openalex.org/I1290206253"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Jinyu Li","raw_affiliation_strings":["Microsoft Speech and Language Group"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Microsoft Speech and Language Group","institution_ids":["https://openalex.org/I1290206253"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101607148","display_name":"Liang Lu","orcid":"https://orcid.org/0000-0003-4005-679X"},"institutions":[{"id":"https://openalex.org/I1290206253","display_name":"Microsoft (United States)","ror":"https://ror.org/00d0nc645","country_code":"US","type":"company","lineage":["https://openalex.org/I1290206253"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Liang Lu","raw_affiliation_strings":["Microsoft Speech and Language Group"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Microsoft Speech and Language Group","institution_ids":["https://openalex.org/I1290206253"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5022890229","display_name":"Changliang Liu","orcid":"https://orcid.org/0009-0005-8201-0871"},"institutions":[{"id":"https://openalex.org/I1290206253","display_name":"Microsoft (United States)","ror":"https://ror.org/00d0nc645","country_code":"US","type":"company","lineage":["https://openalex.org/I1290206253"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Changliang Liu","raw_affiliation_strings":["Microsoft Speech and Language Group"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Microsoft Speech and Language Group","institution_ids":["https://openalex.org/I1290206253"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5077401426","display_name":"Yifan Gong","orcid":"https://orcid.org/0000-0001-8786-3391"},"institutions":[{"id":"https://openalex.org/I1290206253","display_name":"Microsoft (United States)","ror":"https://ror.org/00d0nc645","country_code":"US","type":"company","lineage":["https://openalex.org/I1290206253"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Yifan Gong","raw_affiliation_strings":["Microsoft Speech and Language Group"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Microsoft Speech and Language Group","institution_ids":["https://openalex.org/I1290206253"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I1290206253"],"apc_list":null,"apc_paid":null,"fwci":2.2962,"has_fulltext":false,"cited_by_count":22,"citation_normalized_percentile":{"value":0.91635858,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":90,"max":99},"biblio":{"volume":"5","issue":null,"first_page":"6550","last_page":"6554"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10201","display_name":"Speech Recognition and Synthesis","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"}},"topics":[{"id":"https://openalex.org/T10201","display_name":"Speech Recognition and Synthesis","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/T10028","display_name":"Topic Modeling","score":0.9977999925613403,"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":0.9926000237464905,"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/trajectory","display_name":"Trajectory","score":0.8643014430999756},{"id":"https://openalex.org/keywords/context","display_name":"Context (archaeology)","score":0.7202500700950623},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6955381631851196},{"id":"https://openalex.org/keywords/layer","display_name":"Layer (electronics)","score":0.6763917803764343},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5347138047218323},{"id":"https://openalex.org/keywords/frame","display_name":"Frame (networking)","score":0.45549875497817993},{"id":"https://openalex.org/keywords/geology","display_name":"Geology","score":0.1010693609714508},{"id":"https://openalex.org/keywords/telecommunications","display_name":"Telecommunications","score":0.08132264018058777}],"concepts":[{"id":"https://openalex.org/C13662910","wikidata":"https://www.wikidata.org/wiki/Q193139","display_name":"Trajectory","level":2,"score":0.8643014430999756},{"id":"https://openalex.org/C2779343474","wikidata":"https://www.wikidata.org/wiki/Q3109175","display_name":"Context (archaeology)","level":2,"score":0.7202500700950623},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6955381631851196},{"id":"https://openalex.org/C2779227376","wikidata":"https://www.wikidata.org/wiki/Q6505497","display_name":"Layer (electronics)","level":2,"score":0.6763917803764343},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5347138047218323},{"id":"https://openalex.org/C126042441","wikidata":"https://www.wikidata.org/wiki/Q1324888","display_name":"Frame (networking)","level":2,"score":0.45549875497817993},{"id":"https://openalex.org/C127313418","wikidata":"https://www.wikidata.org/wiki/Q1069","display_name":"Geology","level":0,"score":0.1010693609714508},{"id":"https://openalex.org/C76155785","wikidata":"https://www.wikidata.org/wiki/Q418","display_name":"Telecommunications","level":1,"score":0.08132264018058777},{"id":"https://openalex.org/C178790620","wikidata":"https://www.wikidata.org/wiki/Q11351","display_name":"Organic chemistry","level":1,"score":0.0},{"id":"https://openalex.org/C1276947","wikidata":"https://www.wikidata.org/wiki/Q333","display_name":"Astronomy","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/C185592680","wikidata":"https://www.wikidata.org/wiki/Q2329","display_name":"Chemistry","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.2019.8683783","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icassp.2019.8683783","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":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":44,"referenced_works":["https://openalex.org/W217970951","https://openalex.org/W1600744878","https://openalex.org/W1771459135","https://openalex.org/W1984541135","https://openalex.org/W2061305730","https://openalex.org/W2064675550","https://openalex.org/W2076794394","https://openalex.org/W2089917322","https://openalex.org/W2119615570","https://openalex.org/W2131774270","https://openalex.org/W2143612262","https://openalex.org/W2160815625","https://openalex.org/W2291522532","https://openalex.org/W2293009711","https://openalex.org/W2293634267","https://openalex.org/W2296748324","https://openalex.org/W2396144419","https://openalex.org/W2396384435","https://openalex.org/W2402146185","https://openalex.org/W2403524927","https://openalex.org/W2475988411","https://openalex.org/W2513938599","https://openalex.org/W2586630418","https://openalex.org/W2590320937","https://openalex.org/W2734724284","https://openalex.org/W2735006420","https://openalex.org/W2747006787","https://openalex.org/W2912691643","https://openalex.org/W2962825331","https://openalex.org/W2962962542","https://openalex.org/W2962965465","https://openalex.org/W2963326356","https://openalex.org/W2963917928","https://openalex.org/W2963970535","https://openalex.org/W2964084166","https://openalex.org/W6608710415","https://openalex.org/W6638205174","https://openalex.org/W6696761078","https://openalex.org/W6696934422","https://openalex.org/W6696982659","https://openalex.org/W6697318756","https://openalex.org/W6712930963","https://openalex.org/W6713292810","https://openalex.org/W6749566584"],"related_works":["https://openalex.org/W1941703695","https://openalex.org/W3131574667","https://openalex.org/W4323768008","https://openalex.org/W4248382324","https://openalex.org/W4360995134","https://openalex.org/W2039473718","https://openalex.org/W2387529410","https://openalex.org/W3023605104","https://openalex.org/W3132773133","https://openalex.org/W3092391794"],"abstract_inverted_index":{"In":[0],"our":[1,42],"recent":[2],"work,":[3],"we":[4,68],"proposed":[5],"a":[6],"layer":[7],"trajectory":[8],"long":[9],"short-term":[10],"memory":[11],"(ltLSTM)":[12],"model":[13,30,98],"which":[14],"decouples":[15],"the":[16,36,46,55,60,95,105,120],"tasks":[17],"of":[18,62,75,90],"temporal":[19],"modeling":[20],"and":[21,26,118],"senone":[22],"classification":[23],"with":[24,77,86,99,108,123],"time-LSTMs":[25],"depth-LSTMs.":[27],"The":[28],"ltLSTM":[29,97,107],"achieved":[31],"significant":[32],"accuracy":[33],"improvement":[34],"over":[35],"traditional":[37],"multi-layer":[38],"LSTM":[39,122],"models":[40],"from":[41,80],"previous":[43],"study.":[44],"Considering":[45],"future":[47,100],"context":[48,101],"frames":[49,102],"carrying":[50],"valuable":[51],"information":[52,76],"for":[53],"predicting":[54],"target":[56],"label":[57],"evidenced":[58],"by":[59],"success":[61],"bi-directional":[63],"LSTMs,":[64],"in":[65],"this":[66,73],"work":[67],"investigate":[69],"how":[70],"to":[71,110,125],"incorporate":[72],"kind":[74],"hidden":[78],"vectors":[79],"either":[81],"time-LSTM":[82],"or":[83],"depth-LSTM.":[84],"Trained":[85],"30":[87],"thousand":[88],"hours":[89],"EN-US":[91],"Microsoft":[92],"internal":[93],"data,":[94],"best":[96],"can":[103],"improve":[104,119],"baseline":[106,121],"up":[109,124],"11.5%":[111],"relative":[112,127],"word":[113],"error":[114],"rate":[115],"(WER)":[116],"reduction":[117,129],"24.6%":[126],"WER":[128],"across":[130],"different":[131],"tasks.":[132]},"counts_by_year":[{"year":2023,"cited_by_count":1},{"year":2021,"cited_by_count":5},{"year":2020,"cited_by_count":12},{"year":2019,"cited_by_count":4}],"updated_date":"2026-07-29T14:22:42.915294","created_date":"2025-10-10T00:00:00"}