{"id":"https://openalex.org/W2900209846","doi":"https://doi.org/10.1109/icassp.2019.8682782","title":"Promising Accurate Prefix Boosting for Sequence-to-sequence ASR","display_name":"Promising Accurate Prefix Boosting for Sequence-to-sequence ASR","publication_year":2019,"publication_date":"2019-04-16","ids":{"openalex":"https://openalex.org/W2900209846","doi":"https://doi.org/10.1109/icassp.2019.8682782","mag":"2900209846"},"language":"en","primary_location":{"id":"doi:10.1109/icassp.2019.8682782","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icassp.2019.8682782","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/A5064113992","display_name":"Murali Karthick Baskar","orcid":"https://orcid.org/0000-0002-9396-6319"},"institutions":[{"id":"https://openalex.org/I60587646","display_name":"Brno University of Technology","ror":"https://ror.org/03613d656","country_code":"CZ","type":"education","lineage":["https://openalex.org/I60587646"]}],"countries":["CZ"],"is_corresponding":false,"raw_author_name":"Murali Karthick Baskar","raw_affiliation_strings":["Brno University of Technology"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Brno University of Technology","institution_ids":["https://openalex.org/I60587646"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5042273299","display_name":"Luk\u00e1\u0161 Burget","orcid":"https://orcid.org/0000-0002-4951-5908"},"institutions":[{"id":"https://openalex.org/I60587646","display_name":"Brno University of Technology","ror":"https://ror.org/03613d656","country_code":"CZ","type":"education","lineage":["https://openalex.org/I60587646"]}],"countries":["CZ"],"is_corresponding":false,"raw_author_name":"Lukas Burget","raw_affiliation_strings":["Brno University of Technology"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Brno University of Technology","institution_ids":["https://openalex.org/I60587646"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5001291873","display_name":"Shinji Watanabe","orcid":"https://orcid.org/0000-0002-5970-8631"},"institutions":[{"id":"https://openalex.org/I145311948","display_name":"Johns Hopkins University","ror":"https://ror.org/00za53h95","country_code":"US","type":"education","lineage":["https://openalex.org/I145311948"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Shinji Watanabe","raw_affiliation_strings":["Johns Hopkins University"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Johns Hopkins University","institution_ids":["https://openalex.org/I145311948"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5065253688","display_name":"Martin Karafi\u00e1t","orcid":"https://orcid.org/0000-0001-6474-8366"},"institutions":[{"id":"https://openalex.org/I60587646","display_name":"Brno University of Technology","ror":"https://ror.org/03613d656","country_code":"CZ","type":"education","lineage":["https://openalex.org/I60587646"]}],"countries":["CZ"],"is_corresponding":false,"raw_author_name":"Martin Karafiat","raw_affiliation_strings":["Brno University of Technology"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Brno University of Technology","institution_ids":["https://openalex.org/I60587646"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5087554069","display_name":"Takaaki Hori","orcid":"https://orcid.org/0000-0003-4560-8039"},"institutions":[{"id":"https://openalex.org/I4210133125","display_name":"Mitsubishi Electric (Japan)","ror":"https://ror.org/033y26782","country_code":"JP","type":"company","lineage":["https://openalex.org/I1306287861","https://openalex.org/I4210133125"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Takaaki Hori","raw_affiliation_strings":["Mitsubishi Electric Research Laboratories (MERL)"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Mitsubishi Electric Research Laboratories (MERL)","institution_ids":["https://openalex.org/I4210133125"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5045539248","display_name":"Ja\u0148 \u010cernock\u00fd","orcid":"https://orcid.org/0000-0002-8800-0210"},"institutions":[{"id":"https://openalex.org/I60587646","display_name":"Brno University of Technology","ror":"https://ror.org/03613d656","country_code":"CZ","type":"education","lineage":["https://openalex.org/I60587646"]}],"countries":["CZ"],"is_corresponding":false,"raw_author_name":"Jan Honza Cernocky","raw_affiliation_strings":["Brno University of Technology"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Brno University of Technology","institution_ids":["https://openalex.org/I60587646"]}]}],"institutions":[],"countries_distinct_count":3,"institutions_distinct_count":3,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.9841,"has_fulltext":false,"cited_by_count":11,"citation_normalized_percentile":{"value":0.81194685,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":97},"biblio":{"volume":null,"issue":null,"first_page":"5646","last_page":"5650"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10201","display_name":"Speech Recognition and Synthesis","score":0.9986000061035156,"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":0.9986000061035156,"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/T12326","display_name":"Network Packet Processing and Optimization","score":0.996999979019165,"subfield":{"id":"https://openalex.org/subfields/1708","display_name":"Hardware and Architecture"},"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":0.9962999820709229,"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/prefix","display_name":"Prefix","score":0.8903161287307739},{"id":"https://openalex.org/keywords/boosting","display_name":"Boosting (machine learning)","score":0.8374214172363281},{"id":"https://openalex.org/keywords/sequence","display_name":"Sequence (biology)","score":0.7202944755554199},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6304076910018921},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.4125983417034149},{"id":"https://openalex.org/keywords/genetics","display_name":"Genetics","score":0.05716681480407715},{"id":"https://openalex.org/keywords/biology","display_name":"Biology","score":0.04684561491012573}],"concepts":[{"id":"https://openalex.org/C141603448","wikidata":"https://www.wikidata.org/wiki/Q134830","display_name":"Prefix","level":2,"score":0.8903161287307739},{"id":"https://openalex.org/C46686674","wikidata":"https://www.wikidata.org/wiki/Q466303","display_name":"Boosting (machine learning)","level":2,"score":0.8374214172363281},{"id":"https://openalex.org/C2778112365","wikidata":"https://www.wikidata.org/wiki/Q3511065","display_name":"Sequence (biology)","level":2,"score":0.7202944755554199},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6304076910018921},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4125983417034149},{"id":"https://openalex.org/C54355233","wikidata":"https://www.wikidata.org/wiki/Q7162","display_name":"Genetics","level":1,"score":0.05716681480407715},{"id":"https://openalex.org/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","level":0,"score":0.04684561491012573},{"id":"https://openalex.org/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","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:10.1109/icassp.2019.8682782","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icassp.2019.8682782","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":[{"display_name":"Reduced inequalities","score":0.7099999785423279,"id":"https://metadata.un.org/sdg/10"}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":52,"referenced_works":["https://openalex.org/W6908809","https://openalex.org/W179875071","https://openalex.org/W648786980","https://openalex.org/W1522301498","https://openalex.org/W1586532344","https://openalex.org/W1987238397","https://openalex.org/W2016589492","https://openalex.org/W2024490156","https://openalex.org/W2064675550","https://openalex.org/W2102113734","https://openalex.org/W2105842272","https://openalex.org/W2125234026","https://openalex.org/W2131342762","https://openalex.org/W2131774270","https://openalex.org/W2133564696","https://openalex.org/W2150907703","https://openalex.org/W2158349948","https://openalex.org/W2160668810","https://openalex.org/W2176263492","https://openalex.org/W2180816288","https://openalex.org/W2487501366","https://openalex.org/W2530876040","https://openalex.org/W2746192915","https://openalex.org/W2766219058","https://openalex.org/W2886180730","https://openalex.org/W2889282842","https://openalex.org/W2892124901","https://openalex.org/W2962780374","https://openalex.org/W2962826786","https://openalex.org/W2963248296","https://openalex.org/W2963620441","https://openalex.org/W2963742216","https://openalex.org/W2963747784","https://openalex.org/W2964121744","https://openalex.org/W2964308564","https://openalex.org/W2964352247","https://openalex.org/W4289440825","https://openalex.org/W6600284362","https://openalex.org/W6607333740","https://openalex.org/W6621543089","https://openalex.org/W6631190155","https://openalex.org/W6635078382","https://openalex.org/W6675365184","https://openalex.org/W6675783020","https://openalex.org/W6678457041","https://openalex.org/W6679434410","https://openalex.org/W6682398751","https://openalex.org/W6683880582","https://openalex.org/W6685322675","https://openalex.org/W6686002079","https://openalex.org/W6722524744","https://openalex.org/W6754576867"],"related_works":["https://openalex.org/W2748952813","https://openalex.org/W2142481367","https://openalex.org/W3196321793","https://openalex.org/W3080705045","https://openalex.org/W2385527937","https://openalex.org/W2005880840","https://openalex.org/W2507465767","https://openalex.org/W4385305499","https://openalex.org/W4245066656","https://openalex.org/W2373597927"],"abstract_inverted_index":{"In":[0],"this":[1],"paper,":[2],"we":[3],"present":[4],"promising":[5],"accurate":[6],"prefix":[7],"boosting":[8],"(PAPB),":[9],"a":[10],"discriminative":[11],"training":[12,26,32,52],"technique":[13],"for":[14],"attention":[15],"based":[16],"sequence-to-sequence":[17],"(seq2seq)":[18],"ASR.":[19],"PAPB":[20,62],"is":[21],"devised":[22],"to":[23,48],"unify":[24],"the":[25,36],"and":[27,69,73],"testing":[28],"scheme":[29],"effectively.":[30],"The":[31,51],"procedure":[33],"involves":[34],"maximizing":[35],"score":[37],"of":[38,57],"each":[39],"partial":[40],"correct":[41],"sequence":[42],"obtained":[43],"during":[44],"beam":[45],"search":[46],"compared":[47],"other":[49],"hypotheses.":[50],"objective":[53],"also":[54],"includes":[55],"minimization":[56],"token":[58],"(character)":[59],"error":[60],"rate.":[61],"shows":[63],"its":[64],"efficacy":[65],"by":[66],"achieving":[67],"10.8%":[68],"3.8%":[70],"WER":[71],"with":[72],"without":[74],"external":[75],"RNNLM":[76],"respectively":[77],"on":[78],"Wall":[79],"Street":[80],"Journal":[81],"dataset.":[82]},"counts_by_year":[{"year":2024,"cited_by_count":1},{"year":2023,"cited_by_count":1},{"year":2022,"cited_by_count":1},{"year":2021,"cited_by_count":4},{"year":2020,"cited_by_count":2},{"year":2019,"cited_by_count":2}],"updated_date":"2026-07-29T14:22:42.915294","created_date":"2025-10-10T00:00:00"}