{"id":"https://openalex.org/W2951444698","doi":"https://doi.org/10.1109/access.2019.2922617","title":"End-to-End Speech Recognition Sequence Training With Reinforcement Learning","display_name":"End-to-End Speech Recognition Sequence Training With Reinforcement Learning","publication_year":2019,"publication_date":"2019-01-01","ids":{"openalex":"https://openalex.org/W2951444698","doi":"https://doi.org/10.1109/access.2019.2922617","mag":"2951444698"},"language":"en","primary_location":{"id":"doi:10.1109/access.2019.2922617","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2019.2922617","pdf_url":"https://ieeexplore.ieee.org/ielx7/6287639/8600701/08735756.pdf","source":{"id":"https://openalex.org/S2485537415","display_name":"IEEE Access","issn_l":"2169-3536","issn":["2169-3536"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Access","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","doaj"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://ieeexplore.ieee.org/ielx7/6287639/8600701/08735756.pdf","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5038296765","display_name":"Andros Tjandra","orcid":"https://orcid.org/0000-0003-1246-5908"},"institutions":[{"id":"https://openalex.org/I75917431","display_name":"Nara Institute of Science and Technology","ror":"https://ror.org/05bhada84","country_code":"JP","type":"education","lineage":["https://openalex.org/I75917431"]}],"countries":["JP"],"is_corresponding":true,"raw_author_name":"Andros Tjandra","raw_affiliation_strings":["Nara Institute of Science and Technology, Nara, Japan"],"affiliations":[{"raw_affiliation_string":"Nara Institute of Science and Technology, Nara, Japan","institution_ids":["https://openalex.org/I75917431"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5040108974","display_name":"Sakriani Sakti","orcid":"https://orcid.org/0000-0001-5509-8963"},"institutions":[{"id":"https://openalex.org/I75917431","display_name":"Nara Institute of Science and Technology","ror":"https://ror.org/05bhada84","country_code":"JP","type":"education","lineage":["https://openalex.org/I75917431"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Sakriani Sakti","raw_affiliation_strings":["Nara Institute of Science and Technology, Nara, Japan"],"affiliations":[{"raw_affiliation_string":"Nara Institute of Science and Technology, Nara, Japan","institution_ids":["https://openalex.org/I75917431"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5020994673","display_name":"Satoshi Nakamura","orcid":"https://orcid.org/0000-0001-6956-3803"},"institutions":[{"id":"https://openalex.org/I75917431","display_name":"Nara Institute of Science and Technology","ror":"https://ror.org/05bhada84","country_code":"JP","type":"education","lineage":["https://openalex.org/I75917431"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Satoshi Nakamura","raw_affiliation_strings":["Nara Institute of Science and Technology, Nara, Japan"],"affiliations":[{"raw_affiliation_string":"Nara Institute of Science and Technology, Nara, Japan","institution_ids":["https://openalex.org/I75917431"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5038296765"],"corresponding_institution_ids":["https://openalex.org/I75917431"],"apc_list":{"value":1850,"currency":"USD","value_usd":1850},"apc_paid":{"value":1850,"currency":"USD","value_usd":1850},"fwci":0.7226,"has_fulltext":true,"cited_by_count":12,"citation_normalized_percentile":{"value":0.78385502,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":97},"biblio":{"volume":"7","issue":null,"first_page":"79758","last_page":"79769"},"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/T10028","display_name":"Topic Modeling","score":0.9973999857902527,"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":0.996999979019165,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.8103824853897095},{"id":"https://openalex.org/keywords/inference","display_name":"Inference","score":0.5885000228881836},{"id":"https://openalex.org/keywords/ground-truth","display_name":"Ground truth","score":0.5489729046821594},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5399025082588196},{"id":"https://openalex.org/keywords/reinforcement-learning","display_name":"Reinforcement learning","score":0.5317515134811401},{"id":"https://openalex.org/keywords/speech-recognition","display_name":"Speech recognition","score":0.5193658471107483},{"id":"https://openalex.org/keywords/decoding-methods","display_name":"Decoding methods","score":0.5168881416320801},{"id":"https://openalex.org/keywords/performance-metric","display_name":"Performance metric","score":0.5125622749328613},{"id":"https://openalex.org/keywords/language-model","display_name":"Language model","score":0.49491065740585327},{"id":"https://openalex.org/keywords/metric","display_name":"Metric (unit)","score":0.4501146078109741},{"id":"https://openalex.org/keywords/word-error-rate","display_name":"Word error rate","score":0.4499469995498657},{"id":"https://openalex.org/keywords/pipeline","display_name":"Pipeline (software)","score":0.43792983889579773},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.3887365460395813},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.1766573190689087}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8103824853897095},{"id":"https://openalex.org/C2776214188","wikidata":"https://www.wikidata.org/wiki/Q408386","display_name":"Inference","level":2,"score":0.5885000228881836},{"id":"https://openalex.org/C146849305","wikidata":"https://www.wikidata.org/wiki/Q370766","display_name":"Ground truth","level":2,"score":0.5489729046821594},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5399025082588196},{"id":"https://openalex.org/C97541855","wikidata":"https://www.wikidata.org/wiki/Q830687","display_name":"Reinforcement learning","level":2,"score":0.5317515134811401},{"id":"https://openalex.org/C28490314","wikidata":"https://www.wikidata.org/wiki/Q189436","display_name":"Speech recognition","level":1,"score":0.5193658471107483},{"id":"https://openalex.org/C57273362","wikidata":"https://www.wikidata.org/wiki/Q576722","display_name":"Decoding methods","level":2,"score":0.5168881416320801},{"id":"https://openalex.org/C2780898871","wikidata":"https://www.wikidata.org/wiki/Q860554","display_name":"Performance metric","level":2,"score":0.5125622749328613},{"id":"https://openalex.org/C137293760","wikidata":"https://www.wikidata.org/wiki/Q3621696","display_name":"Language model","level":2,"score":0.49491065740585327},{"id":"https://openalex.org/C176217482","wikidata":"https://www.wikidata.org/wiki/Q860554","display_name":"Metric (unit)","level":2,"score":0.4501146078109741},{"id":"https://openalex.org/C40969351","wikidata":"https://www.wikidata.org/wiki/Q3516228","display_name":"Word error rate","level":2,"score":0.4499469995498657},{"id":"https://openalex.org/C43521106","wikidata":"https://www.wikidata.org/wiki/Q2165493","display_name":"Pipeline (software)","level":2,"score":0.43792983889579773},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.3887365460395813},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.1766573190689087},{"id":"https://openalex.org/C21547014","wikidata":"https://www.wikidata.org/wiki/Q1423657","display_name":"Operations management","level":1,"score":0.0},{"id":"https://openalex.org/C162324750","wikidata":"https://www.wikidata.org/wiki/Q8134","display_name":"Economics","level":0,"score":0.0},{"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/C187736073","wikidata":"https://www.wikidata.org/wiki/Q2920921","display_name":"Management","level":1,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/access.2019.2922617","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2019.2922617","pdf_url":"https://ieeexplore.ieee.org/ielx7/6287639/8600701/08735756.pdf","source":{"id":"https://openalex.org/S2485537415","display_name":"IEEE Access","issn_l":"2169-3536","issn":["2169-3536"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Access","raw_type":"journal-article"},{"id":"pmh:oai:doaj.org/article:70855970c18b40568b9aa2877c43bc09","is_oa":true,"landing_page_url":"https://doaj.org/article/70855970c18b40568b9aa2877c43bc09","pdf_url":null,"source":{"id":"https://openalex.org/S112646816","display_name":"SHILAP Revista de lepidopterolog\u00eda","issn_l":"0300-5267","issn":["0300-5267","2340-4078"],"is_oa":true,"is_in_doaj":true,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"journal"},"license":"cc-by-sa","license_id":"https://openalex.org/licenses/cc-by-sa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"IEEE Access, Vol 7, Pp 79758-79769 (2019)","raw_type":"article"}],"best_oa_location":{"id":"doi:10.1109/access.2019.2922617","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2019.2922617","pdf_url":"https://ieeexplore.ieee.org/ielx7/6287639/8600701/08735756.pdf","source":{"id":"https://openalex.org/S2485537415","display_name":"IEEE Access","issn_l":"2169-3536","issn":["2169-3536"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Access","raw_type":"journal-article"},"sustainable_development_goals":[{"score":0.41999998688697815,"id":"https://metadata.un.org/sdg/16","display_name":"Peace, Justice and strong institutions"}],"awards":[{"id":"https://openalex.org/G1069223013","display_name":null,"funder_award_id":"JSPS KAKENHI","funder_id":"https://openalex.org/F4320334764","funder_display_name":"Japan Society for the Promotion of Science"},{"id":"https://openalex.org/G1688345242","display_name":null,"funder_award_id":"17H06101","funder_id":"https://openalex.org/F4320334764","funder_display_name":"Japan Society for the Promotion of Science"},{"id":"https://openalex.org/G3459562248","display_name":null,"funder_award_id":"Grant","funder_id":"https://openalex.org/F4320334764","funder_display_name":"Japan Society for the Promotion of Science"},{"id":"https://openalex.org/G4227499671","display_name":null,"funder_award_id":"KAKENHI Grant","funder_id":"https://openalex.org/F4320334764","funder_display_name":"Japan Society for the Promotion of Science"},{"id":"https://openalex.org/G4636223006","display_name":null,"funder_award_id":"JSPS KAK","funder_id":"https://openalex.org/F4320334764","funder_display_name":"Japan Society for the Promotion of Science"},{"id":"https://openalex.org/G4827429566","display_name":null,"funder_award_id":"Grant Numbers","funder_id":"https://openalex.org/F4320334764","funder_display_name":"Japan Society for the Promotion of Science"},{"id":"https://openalex.org/G5786340949","display_name":null,"funder_award_id":"KAKENHI Grant Number","funder_id":"https://openalex.org/F4320334764","funder_display_name":"Japan Society for the Promotion of Science"},{"id":"https://openalex.org/G6616750388","display_name":null,"funder_award_id":"JP17H06101","funder_id":"https://openalex.org/F4320334764","funder_display_name":"Japan Society for the Promotion of Science"},{"id":"https://openalex.org/G8430481527","display_name":null,"funder_award_id":"Number","funder_id":"https://openalex.org/F4320334764","funder_display_name":"Japan Society for the Promotion of Science"},{"id":"https://openalex.org/G8777250574","display_name":"Research for unsupervised acoustic pattern discovery with zero resources","funder_award_id":"17K00237","funder_id":"https://openalex.org/F4320334764","funder_display_name":"Japan Society for the Promotion of Science"},{"id":"https://openalex.org/G947068629","display_name":null,"funder_award_id":"JP17K00237","funder_id":"https://openalex.org/F4320334764","funder_display_name":"Japan Society for the Promotion of Science"}],"funders":[{"id":"https://openalex.org/F4320334764","display_name":"Japan Society for the Promotion of Science","ror":"https://ror.org/00hhkn466"}],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W2951444698.pdf","grobid_xml":"https://content.openalex.org/works/W2951444698.grobid-xml"},"referenced_works_count":57,"referenced_works":["https://openalex.org/W32403112","https://openalex.org/W1514535095","https://openalex.org/W1515851193","https://openalex.org/W1522301498","https://openalex.org/W1524333225","https://openalex.org/W1895577753","https://openalex.org/W1916559533","https://openalex.org/W1921523184","https://openalex.org/W1977655452","https://openalex.org/W2016589492","https://openalex.org/W2024490156","https://openalex.org/W2064675550","https://openalex.org/W2076063813","https://openalex.org/W2101105183","https://openalex.org/W2108682071","https://openalex.org/W2119717200","https://openalex.org/W2129142580","https://openalex.org/W2130942839","https://openalex.org/W2133564696","https://openalex.org/W2142416747","https://openalex.org/W2144499799","https://openalex.org/W2145339207","https://openalex.org/W2160815625","https://openalex.org/W2163068732","https://openalex.org/W2176263492","https://openalex.org/W2257979135","https://openalex.org/W2327501763","https://openalex.org/W2525778437","https://openalex.org/W2526425061","https://openalex.org/W2892124901","https://openalex.org/W2952264928","https://openalex.org/W2962759037","https://openalex.org/W2962765220","https://openalex.org/W2962826786","https://openalex.org/W2963144852","https://openalex.org/W2963167310","https://openalex.org/W2963463964","https://openalex.org/W2963609956","https://openalex.org/W2963929190","https://openalex.org/W2964308564","https://openalex.org/W3211848854","https://openalex.org/W4205130185","https://openalex.org/W6630875275","https://openalex.org/W6631190155","https://openalex.org/W6631362777","https://openalex.org/W6640185926","https://openalex.org/W6676023451","https://openalex.org/W6677929280","https://openalex.org/W6679434410","https://openalex.org/W6679436768","https://openalex.org/W6683794156","https://openalex.org/W6685322675","https://openalex.org/W6736996214","https://openalex.org/W6738974909","https://openalex.org/W6745177358","https://openalex.org/W6745628346","https://openalex.org/W6898505805"],"related_works":["https://openalex.org/W1566315437","https://openalex.org/W2594897229","https://openalex.org/W4221142855","https://openalex.org/W2151348424","https://openalex.org/W2050138804","https://openalex.org/W4290708361","https://openalex.org/W2129812225","https://openalex.org/W2523799048","https://openalex.org/W2155620340","https://openalex.org/W1494910745"],"abstract_inverted_index":{"End-to-end":[0],"sequence":[1,76],"modeling":[2],"has":[3,160],"become":[4],"a":[5,188,218],"popular":[6],"choice":[7],"for":[8,139],"automatic":[9],"speech":[10,55],"recognition":[11],"(ASR)":[12],"because":[13,65,95],"of":[14,96,146],"the":[15,20,33,39,44,50,58,61,66,74,86,97,105,115,119,127,147,157,164,167,180,185,193,203,213],"simpler":[16],"pipeline":[17],"compared":[18,216],"to":[19,73,217],"conventional":[21],"system":[22],"and":[23,54,84,101,174,225],"its":[24,176],"excellent":[25],"performance.":[26],"However,":[27,118],"there":[28],"are":[29,47],"several":[30,161],"drawbacks":[31],"in":[32],"end-to-end":[34,141],"ASR":[35,120,142,194],"model":[36,67,143,155,165,186,214,219],"training":[37,100,106],"where":[38],"current":[40],"time-step":[41],"prediction":[42],"on":[43,126,202],"target":[45,75],"side":[46],"conditioned":[48],"with":[49,144,187,192,222],"ground":[51],"truth":[52],"transcription":[53],"features.":[56],"In":[57,104],"inference":[59,168],"stage,":[60,107],"condition":[62],"is":[63,93,112,123],"different":[64],"does":[68],"not":[69],"have":[70],"any":[71,79],"access":[72],"ground-truth,":[77],"thus":[78],"mistakes":[80],"might":[81],"be":[82],"accumulated":[83],"degrade":[85],"decoding":[87],"result":[88,204],"over":[89],"time.":[90],"Another":[91],"issue":[92],"raised":[94],"discrepancy":[98],"between":[99],"evaluation":[102,195],"objective.":[103],"maximum":[108,226],"likelihood":[109,227],"estimation":[110],"criterion":[111],"used":[113],"as":[114,179],"objective":[116,228],"function.":[117,229],"systems":[121],"quality":[122],"evaluated":[124],"based":[125],"word":[128],"error":[129],"rate":[130],"via":[131],"Levenshtein":[132,199],"distance.":[133],"Therefore,":[134],"we":[135],"present":[136],"an":[137],"alternative":[138],"optimizing":[140],"one":[145],"reinforcement":[148],"learning":[149],"method":[150,210],"called":[151],"policy":[152],"gradient.":[153],"The":[154],"trained":[156,220],"proposed":[158,209],"approach":[159],"advantages:":[162],"(1)":[163],"simulates":[166],"stage":[169],"by":[170],"free":[171],"sampling":[172],"process":[173],"uses":[175],"own":[177],"sample":[178],"input,":[181],"and;":[182],"(2)":[183],"optimize":[184],"reward":[189],"function":[190],"correlated":[191],"metric":[196],"(e.g.,":[197],"negative":[198],"distance).":[200],"Based":[201],"from":[205],"our":[206,208],"experiment,":[207],"significantly":[211],"improve":[212],"performance":[215],"only":[221],"teacher":[223],"forcing":[224]},"counts_by_year":[{"year":2025,"cited_by_count":1},{"year":2024,"cited_by_count":3},{"year":2023,"cited_by_count":3},{"year":2022,"cited_by_count":1},{"year":2021,"cited_by_count":3},{"year":2020,"cited_by_count":1}],"updated_date":"2026-04-15T08:11:43.952461","created_date":"2025-10-10T00:00:00"}
