{"id":"https://openalex.org/W2394835536","doi":"https://doi.org/10.21437/interspeech.2015-475","title":"Applying GPGPU to recurrent neural network language model based fast network search in the real-time LVCSR","display_name":"Applying GPGPU to recurrent neural network language model based fast network search in the real-time LVCSR","publication_year":2015,"publication_date":"2015-09-06","ids":{"openalex":"https://openalex.org/W2394835536","doi":"https://doi.org/10.21437/interspeech.2015-475","mag":"2394835536"},"language":"en","primary_location":{"id":"doi:10.21437/interspeech.2015-475","is_oa":false,"landing_page_url":"https://doi.org/10.21437/interspeech.2015-475","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Interspeech 2015","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/A5100747695","display_name":"Kyung-Min Lee","orcid":"https://orcid.org/0000-0003-3102-4550"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Kyungmin Lee","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5024567256","display_name":"Chiyoun Park","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Chiyoun Park","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101635106","display_name":"Il-Hwan Kim","orcid":"https://orcid.org/0000-0003-3554-8845"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Ilhwan Kim","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100615740","display_name":"Namhoon Kim","orcid":"https://orcid.org/0000-0001-8504-4245"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Namhoon Kim","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5100329194","display_name":"Jaewon Lee","orcid":"https://orcid.org/0000-0002-0768-384X"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Jaewon Lee","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":0,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.2058,"has_fulltext":false,"cited_by_count":5,"citation_normalized_percentile":{"value":0.51310044,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":96},"biblio":{"volume":null,"issue":null,"first_page":"2102","last_page":"2106"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10181","display_name":"Natural Language Processing Techniques","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"}},"topics":[{"id":"https://openalex.org/T10181","display_name":"Natural Language Processing Techniques","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"}},{"id":"https://openalex.org/T10201","display_name":"Speech Recognition and Synthesis","score":0.996999979019165,"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":0.9872000217437744,"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":0.928192675113678},{"id":"https://openalex.org/keywords/recurrent-neural-network","display_name":"Recurrent neural network","score":0.6492131948471069},{"id":"https://openalex.org/keywords/language-model","display_name":"Language model","score":0.60288405418396},{"id":"https://openalex.org/keywords/vocabulary","display_name":"Vocabulary","score":0.562805712223053},{"id":"https://openalex.org/keywords/general-purpose-computing-on-graphics-processing-units","display_name":"General-purpose computing on graphics processing units","score":0.5405181646347046},{"id":"https://openalex.org/keywords/word-error-rate","display_name":"Word error rate","score":0.5309618711471558},{"id":"https://openalex.org/keywords/graph","display_name":"Graph","score":0.49510326981544495},{"id":"https://openalex.org/keywords/speedup","display_name":"Speedup","score":0.48953017592430115},{"id":"https://openalex.org/keywords/speech-recognition","display_name":"Speech recognition","score":0.43325257301330566},{"id":"https://openalex.org/keywords/computation","display_name":"Computation","score":0.4311874508857727},{"id":"https://openalex.org/keywords/decoding-methods","display_name":"Decoding methods","score":0.4104114770889282},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.3995663523674011},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.39663130044937134},{"id":"https://openalex.org/keywords/parallel-computing","display_name":"Parallel computing","score":0.3302990794181824},{"id":"https://openalex.org/keywords/graphics","display_name":"Graphics","score":0.1996327042579651},{"id":"https://openalex.org/keywords/theoretical-computer-science","display_name":"Theoretical computer science","score":0.17050272226333618},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.15092426538467407}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.928192675113678},{"id":"https://openalex.org/C147168706","wikidata":"https://www.wikidata.org/wiki/Q1457734","display_name":"Recurrent neural network","level":3,"score":0.6492131948471069},{"id":"https://openalex.org/C137293760","wikidata":"https://www.wikidata.org/wiki/Q3621696","display_name":"Language model","level":2,"score":0.60288405418396},{"id":"https://openalex.org/C2777601683","wikidata":"https://www.wikidata.org/wiki/Q6499736","display_name":"Vocabulary","level":2,"score":0.562805712223053},{"id":"https://openalex.org/C50630238","wikidata":"https://www.wikidata.org/wiki/Q971505","display_name":"General-purpose computing on graphics processing units","level":3,"score":0.5405181646347046},{"id":"https://openalex.org/C40969351","wikidata":"https://www.wikidata.org/wiki/Q3516228","display_name":"Word error rate","level":2,"score":0.5309618711471558},{"id":"https://openalex.org/C132525143","wikidata":"https://www.wikidata.org/wiki/Q141488","display_name":"Graph","level":2,"score":0.49510326981544495},{"id":"https://openalex.org/C68339613","wikidata":"https://www.wikidata.org/wiki/Q1549489","display_name":"Speedup","level":2,"score":0.48953017592430115},{"id":"https://openalex.org/C28490314","wikidata":"https://www.wikidata.org/wiki/Q189436","display_name":"Speech recognition","level":1,"score":0.43325257301330566},{"id":"https://openalex.org/C45374587","wikidata":"https://www.wikidata.org/wiki/Q12525525","display_name":"Computation","level":2,"score":0.4311874508857727},{"id":"https://openalex.org/C57273362","wikidata":"https://www.wikidata.org/wiki/Q576722","display_name":"Decoding methods","level":2,"score":0.4104114770889282},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.3995663523674011},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.39663130044937134},{"id":"https://openalex.org/C173608175","wikidata":"https://www.wikidata.org/wiki/Q232661","display_name":"Parallel computing","level":1,"score":0.3302990794181824},{"id":"https://openalex.org/C21442007","wikidata":"https://www.wikidata.org/wiki/Q1027879","display_name":"Graphics","level":2,"score":0.1996327042579651},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.17050272226333618},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.15092426538467407},{"id":"https://openalex.org/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","level":1,"score":0.0},{"id":"https://openalex.org/C121684516","wikidata":"https://www.wikidata.org/wiki/Q7600677","display_name":"Computer graphics (images)","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}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.21437/interspeech.2015-475","is_oa":false,"landing_page_url":"https://doi.org/10.21437/interspeech.2015-475","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Interspeech 2015","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Quality Education","score":0.7699999809265137,"id":"https://metadata.un.org/sdg/4"}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":["https://openalex.org/W1980160788","https://openalex.org/W2495256954","https://openalex.org/W2259317772","https://openalex.org/W2594897229","https://openalex.org/W2151348424","https://openalex.org/W4221142855","https://openalex.org/W2050138804","https://openalex.org/W4290708361","https://openalex.org/W2129812225","https://openalex.org/W26527944"],"abstract_inverted_index":{"Recurrent":[0],"Neural":[1],"Network":[2],"Language":[3],"Models":[4],"(RNNLMs)":[5],"have":[6,81],"started":[7],"to":[8,18,37,48,76,131],"be":[9,132],"used":[10],"in":[11,33,121],"various":[12,122],"fields":[13],"of":[14,27,52,73,93,138],"speech":[15],"recognition":[16],"due":[17],"their":[19],"outstanding":[20],"performance.":[21],"However,":[22],"the":[23,35,50,60,114,118,126],"high":[24],"computational":[25],"complexity":[26],"RNNLMs":[28],"has":[29],"been":[30],"a":[31,38,70],"hurdle":[32],"applying":[34,74],"RNNLM":[36],"real-time":[39,119],"Large":[40],"Vocabulary":[41],"Continuous":[42],"Speech":[43],"Recognition":[44],"(LVCSR).":[45],"In":[46],"order":[47],"accelerate":[49],"speed":[51,120],"RNNLM-based":[53,77],"network":[54],"searches":[55],"during":[56],"decoding,":[57],"we":[58],"apply":[59],"General":[61],"Purpose":[62],"Graphic":[63],"Processing":[64],"Units":[65],"(GPGPUs).":[66],"This":[67],"paper":[68],"proposes":[69],"novel":[71],"method":[72],"GPGPUs":[75,96],"graph":[78],"traversals.":[79],"We":[80],"achieved":[82],"our":[83],"goal":[84],"by":[85],"reducing":[86],"redundant":[87],"computations":[88],"on":[89,104],"CPUs":[90],"and":[91,97,108],"amount":[92],"transfer":[94],"between":[95],"CPUs.":[98],"The":[99],"proposed":[100,115],"approach":[101,116],"was":[102],"evaluated":[103],"both":[105],"WSJ":[106],"corpus":[107],"in-house":[109],"data.":[110],"Experiments":[111],"shows":[112],"that":[113,137],"achieves":[117],"circumstances":[123],"while":[124],"maintaining":[125],"Word":[127],"Error":[128],"Rate":[129],"(WER)":[130],"relatively":[133],"10%":[134],"lower":[135],"than":[136],"n-gram":[139],"models.":[140]},"counts_by_year":[{"year":2021,"cited_by_count":1},{"year":2020,"cited_by_count":1},{"year":2019,"cited_by_count":2},{"year":2018,"cited_by_count":1}],"updated_date":"2026-07-29T14:22:42.915294","created_date":"2025-10-10T00:00:00"}