{"id":"https://openalex.org/W2168371706","doi":"https://doi.org/10.1109/icassp.2012.6288849","title":"A general discriminative training algorithm for speech recognition using weighted finite-state transducers","display_name":"A general discriminative training algorithm for speech recognition using weighted finite-state transducers","publication_year":2012,"publication_date":"2012-03-01","ids":{"openalex":"https://openalex.org/W2168371706","doi":"https://doi.org/10.1109/icassp.2012.6288849","mag":"2168371706"},"language":"en","primary_location":{"id":"doi:10.1109/icassp.2012.6288849","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icassp.2012.6288849","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2012 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/A5100702071","display_name":"Yong Zhao","orcid":"https://orcid.org/0000-0003-2644-952X"},"institutions":[{"id":"https://openalex.org/I130701444","display_name":"Georgia Institute of Technology","ror":"https://ror.org/01zkghx44","country_code":"US","type":"education","lineage":["https://openalex.org/I130701444"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Yong Zhao","raw_affiliation_strings":["Department of Electrical and Computer Engineering, Georgia Institute of Technology, Atlanta, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Electrical and Computer Engineering, Georgia Institute of Technology, Atlanta, USA","institution_ids":["https://openalex.org/I130701444"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5060308914","display_name":"Andrej Ljolje","orcid":null},"institutions":[{"id":"https://openalex.org/I1283103587","display_name":"AT&T (United States)","ror":"https://ror.org/02bbd5539","country_code":"US","type":"company","lineage":["https://openalex.org/I1283103587"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Andrej Ljolje","raw_affiliation_strings":["AT&T Labs-Research, Florham Park, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"AT&T Labs-Research, Florham Park, USA","institution_ids":["https://openalex.org/I1283103587"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5021056932","display_name":"Diamantino Caseiro","orcid":null},"institutions":[{"id":"https://openalex.org/I1283103587","display_name":"AT&T (United States)","ror":"https://ror.org/02bbd5539","country_code":"US","type":"company","lineage":["https://openalex.org/I1283103587"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Diamantino Caseiro","raw_affiliation_strings":["AT&T Labs-Research, Florham Park, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"AT&T Labs-Research, Florham Park, USA","institution_ids":["https://openalex.org/I1283103587"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5070867959","display_name":"Biing\u2010Hwang Juang","orcid":"https://orcid.org/0000-0002-5773-5679"},"institutions":[{"id":"https://openalex.org/I130701444","display_name":"Georgia Institute of Technology","ror":"https://ror.org/01zkghx44","country_code":"US","type":"education","lineage":["https://openalex.org/I130701444"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Biing-Hwang Juang","raw_affiliation_strings":["Department of Electrical and Computer Engineering, Georgia Institute of Technology, Atlanta, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Electrical and Computer Engineering, Georgia Institute of Technology, Atlanta, USA","institution_ids":["https://openalex.org/I130701444"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.2602,"has_fulltext":false,"cited_by_count":1,"citation_normalized_percentile":{"value":0.52612925,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":94},"biblio":{"volume":"15","issue":null,"first_page":"4217","last_page":"4220"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10201","display_name":"Speech Recognition and Synthesis","score":0.9998000264167786,"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":0.9998000264167786,"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":0.9965000152587891,"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":0.9943000078201294,"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/discriminative-model","display_name":"Discriminative model","score":0.8357453346252441},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7374191284179688},{"id":"https://openalex.org/keywords/word","display_name":"Word (group theory)","score":0.622052013874054},{"id":"https://openalex.org/keywords/speech-recognition","display_name":"Speech recognition","score":0.6069182753562927},{"id":"https://openalex.org/keywords/hidden-markov-model","display_name":"Hidden Markov model","score":0.5984888672828674},{"id":"https://openalex.org/keywords/word-recognition","display_name":"Word recognition","score":0.4249698221683502},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.3797438144683838},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.33000338077545166},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.15842580795288086},{"id":"https://openalex.org/keywords/reading","display_name":"Reading (process)","score":0.07918685674667358}],"concepts":[{"id":"https://openalex.org/C97931131","wikidata":"https://www.wikidata.org/wiki/Q5282087","display_name":"Discriminative model","level":2,"score":0.8357453346252441},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7374191284179688},{"id":"https://openalex.org/C90805587","wikidata":"https://www.wikidata.org/wiki/Q10944557","display_name":"Word (group theory)","level":2,"score":0.622052013874054},{"id":"https://openalex.org/C28490314","wikidata":"https://www.wikidata.org/wiki/Q189436","display_name":"Speech recognition","level":1,"score":0.6069182753562927},{"id":"https://openalex.org/C23224414","wikidata":"https://www.wikidata.org/wiki/Q176769","display_name":"Hidden Markov model","level":2,"score":0.5984888672828674},{"id":"https://openalex.org/C150856459","wikidata":"https://www.wikidata.org/wiki/Q8034367","display_name":"Word recognition","level":3,"score":0.4249698221683502},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.3797438144683838},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.33000338077545166},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.15842580795288086},{"id":"https://openalex.org/C554936623","wikidata":"https://www.wikidata.org/wiki/Q199657","display_name":"Reading (process)","level":2,"score":0.07918685674667358},{"id":"https://openalex.org/C2524010","wikidata":"https://www.wikidata.org/wiki/Q8087","display_name":"Geometry","level":1,"score":0.0},{"id":"https://openalex.org/C17744445","wikidata":"https://www.wikidata.org/wiki/Q36442","display_name":"Political science","level":0,"score":0.0},{"id":"https://openalex.org/C199539241","wikidata":"https://www.wikidata.org/wiki/Q7748","display_name":"Law","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/icassp.2012.6288849","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icassp.2012.6288849","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2012 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.6800000071525574,"display_name":"Reduced inequalities","id":"https://metadata.un.org/sdg/10"}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":13,"referenced_works":["https://openalex.org/W34922426","https://openalex.org/W181370797","https://openalex.org/W1877570817","https://openalex.org/W1895481600","https://openalex.org/W1979136262","https://openalex.org/W2024539680","https://openalex.org/W2112897804","https://openalex.org/W2144071798","https://openalex.org/W2158289097","https://openalex.org/W2158339352","https://openalex.org/W2158808283","https://openalex.org/W6601431124","https://openalex.org/W6683478398"],"related_works":["https://openalex.org/W2167155152","https://openalex.org/W2136763963","https://openalex.org/W2109705048","https://openalex.org/W2940588515","https://openalex.org/W1909151225","https://openalex.org/W1987783679","https://openalex.org/W2160030256","https://openalex.org/W1521297879","https://openalex.org/W4253235840","https://openalex.org/W3151937861"],"abstract_inverted_index":{"In":[0,26],"this":[1],"paper,":[2],"we":[3],"present":[4],"a":[5,14,49,61,65,72,87,102],"general":[6],"algorithmic":[7],"framework":[8,117],"based":[9],"on":[10,120],"WFSTs":[11],"for":[12,83,105],"implementing":[13],"variety":[15],"of":[16,97,107,115],"discriminative":[17],"training":[18,109],"methods,":[19],"such":[20],"as":[21],"MMI,":[22],"MCE,":[23],"and":[24,41,47,75,127],"MPE/MWE.":[25],"contrast":[27],"to":[28,39,71,101],"the":[29,33,43,53,94,98,108,116],"ordinary":[30],"word":[31,73,77,85],"lattices,":[32],"transducer-based":[34],"lattices":[35],"are":[36,58],"more":[37],"amenable":[38],"representing":[40],"manipulating":[42],"underlying":[44],"hypothesis":[45],"space":[46],"have":[48],"finer":[50],"granularity":[51],"at":[52,64,86],"HMM-state":[54,81],"level.":[55,89],"The":[56,113],"transducers":[57,99],"processed":[59],"into":[60],"two-layer":[62],"hierarchy:":[63],"high":[66],"level,":[67],"it":[68],"is":[69,118],"analogous":[70],"lattice,":[74],"each":[76],"transition":[78],"embodies":[79],"an":[80,130],"subgraph":[82],"that":[84],"lower":[88],"This":[90],"hierarchy":[91],"combined":[92],"with":[93],"appropriate":[95],"customization":[96],"leads":[100],"flexible":[103],"implementation":[104],"all":[106],"criteria":[110],"being":[111],"discussed.":[112],"effectiveness":[114],"verified":[119],"two":[121],"speech":[122],"recognition":[123],"tasks:":[124],"Resource":[125],"Management,":[126],"AT&T":[128],"SCANMail,":[129],"internal":[131],"voicemail-to-text":[132],"task.":[133]},"counts_by_year":[{"year":2013,"cited_by_count":1}],"updated_date":"2026-07-29T14:22:42.915294","created_date":"2025-10-10T00:00:00"}
