{"id":"https://openalex.org/W2140777099","doi":"https://doi.org/10.1109/icassp.2011.5946923","title":"PAC-Bayesian approach for minimization of phoneme error rate","display_name":"PAC-Bayesian approach for minimization of phoneme error rate","publication_year":2011,"publication_date":"2011-05-01","ids":{"openalex":"https://openalex.org/W2140777099","doi":"https://doi.org/10.1109/icassp.2011.5946923","mag":"2140777099"},"language":"en","primary_location":{"id":"doi:10.1109/icassp.2011.5946923","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icassp.2011.5946923","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2011 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)","raw_type":"proceedings-article"},"type":"article","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/A5008847407","display_name":"Joseph Keshet","orcid":"https://orcid.org/0000-0003-2332-5783"},"institutions":[{"id":"https://openalex.org/I160992636","display_name":"Toyota Technological Institute at Chicago","ror":"https://ror.org/02sn5gb64","country_code":"US","type":"education","lineage":["https://openalex.org/I160992636"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Joseph Keshet","raw_affiliation_strings":["Toyota Technological Institute, Chicago, IL, USA","Toyota Technological Institute at Chicago, IL USA"],"affiliations":[{"raw_affiliation_string":"Toyota Technological Institute, Chicago, IL, USA","institution_ids":["https://openalex.org/I160992636"]},{"raw_affiliation_string":"Toyota Technological Institute at Chicago, IL USA","institution_ids":["https://openalex.org/I160992636"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5033089246","display_name":"David McAllester","orcid":null},"institutions":[{"id":"https://openalex.org/I160992636","display_name":"Toyota Technological Institute at Chicago","ror":"https://ror.org/02sn5gb64","country_code":"US","type":"education","lineage":["https://openalex.org/I160992636"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"David McAllester","raw_affiliation_strings":["Toyota Technical Institute, Chicago, IL, USA","Toyota Technological Institute at Chicago, IL USA"],"affiliations":[{"raw_affiliation_string":"Toyota Technical Institute, Chicago, IL, USA","institution_ids":["https://openalex.org/I160992636"]},{"raw_affiliation_string":"Toyota Technological Institute at Chicago, IL USA","institution_ids":["https://openalex.org/I160992636"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5000106487","display_name":"Tamir Hazan","orcid":"https://orcid.org/0000-0003-1652-3845"},"institutions":[{"id":"https://openalex.org/I160992636","display_name":"Toyota Technological Institute at Chicago","ror":"https://ror.org/02sn5gb64","country_code":"US","type":"education","lineage":["https://openalex.org/I160992636"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Tamir Hazan","raw_affiliation_strings":["Toyota Technological Institute, Chicago, IL, USA","Toyota Technological Institute at Chicago, IL USA"],"affiliations":[{"raw_affiliation_string":"Toyota Technological Institute, Chicago, IL, USA","institution_ids":["https://openalex.org/I160992636"]},{"raw_affiliation_string":"Toyota Technological Institute at Chicago, IL USA","institution_ids":["https://openalex.org/I160992636"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5008847407"],"corresponding_institution_ids":["https://openalex.org/I160992636"],"apc_list":null,"apc_paid":null,"fwci":7.4842,"has_fulltext":false,"cited_by_count":34,"citation_normalized_percentile":{"value":0.97151302,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":90,"max":99},"biblio":{"volume":null,"issue":null,"first_page":"2224","last_page":"2227"},"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/T11309","display_name":"Music and Audio Processing","score":0.9998000264167786,"subfield":{"id":"https://openalex.org/subfields/1711","display_name":"Signal Processing"},"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":0.9994999766349792,"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/timit","display_name":"TIMIT","score":0.8526026010513306},{"id":"https://openalex.org/keywords/discriminative-model","display_name":"Discriminative model","score":0.6930257678031921},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6705111265182495},{"id":"https://openalex.org/keywords/word-error-rate","display_name":"Word error rate","score":0.6256516575813293},{"id":"https://openalex.org/keywords/stochastic-gradient-descent","display_name":"Stochastic gradient descent","score":0.5320896506309509},{"id":"https://openalex.org/keywords/bayesian-probability","display_name":"Bayesian probability","score":0.5277493596076965},{"id":"https://openalex.org/keywords/upper-and-lower-bounds","display_name":"Upper and lower bounds","score":0.5261080861091614},{"id":"https://openalex.org/keywords/generalization","display_name":"Generalization","score":0.504597544670105},{"id":"https://openalex.org/keywords/gradient-descent","display_name":"Gradient descent","score":0.46086108684539795},{"id":"https://openalex.org/keywords/speech-recognition","display_name":"Speech recognition","score":0.4573821425437927},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.4480727016925812},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.427178293466568},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.39827755093574524},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.38879817724227905},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.26747655868530273},{"id":"https://openalex.org/keywords/hidden-markov-model","display_name":"Hidden Markov model","score":0.21964186429977417},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.11455035209655762}],"concepts":[{"id":"https://openalex.org/C2778724510","wikidata":"https://www.wikidata.org/wiki/Q7670405","display_name":"TIMIT","level":3,"score":0.8526026010513306},{"id":"https://openalex.org/C97931131","wikidata":"https://www.wikidata.org/wiki/Q5282087","display_name":"Discriminative model","level":2,"score":0.6930257678031921},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6705111265182495},{"id":"https://openalex.org/C40969351","wikidata":"https://www.wikidata.org/wiki/Q3516228","display_name":"Word error rate","level":2,"score":0.6256516575813293},{"id":"https://openalex.org/C206688291","wikidata":"https://www.wikidata.org/wiki/Q7617819","display_name":"Stochastic gradient descent","level":3,"score":0.5320896506309509},{"id":"https://openalex.org/C107673813","wikidata":"https://www.wikidata.org/wiki/Q812534","display_name":"Bayesian probability","level":2,"score":0.5277493596076965},{"id":"https://openalex.org/C77553402","wikidata":"https://www.wikidata.org/wiki/Q13222579","display_name":"Upper and lower bounds","level":2,"score":0.5261080861091614},{"id":"https://openalex.org/C177148314","wikidata":"https://www.wikidata.org/wiki/Q170084","display_name":"Generalization","level":2,"score":0.504597544670105},{"id":"https://openalex.org/C153258448","wikidata":"https://www.wikidata.org/wiki/Q1199743","display_name":"Gradient descent","level":3,"score":0.46086108684539795},{"id":"https://openalex.org/C28490314","wikidata":"https://www.wikidata.org/wiki/Q189436","display_name":"Speech recognition","level":1,"score":0.4573821425437927},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.4480727016925812},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.427178293466568},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.39827755093574524},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.38879817724227905},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.26747655868530273},{"id":"https://openalex.org/C23224414","wikidata":"https://www.wikidata.org/wiki/Q176769","display_name":"Hidden Markov model","level":2,"score":0.21964186429977417},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.11455035209655762},{"id":"https://openalex.org/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","level":1,"score":0.0},{"id":"https://openalex.org/C134306372","wikidata":"https://www.wikidata.org/wiki/Q7754","display_name":"Mathematical analysis","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":2,"locations":[{"id":"doi:10.1109/icassp.2011.5946923","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icassp.2011.5946923","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2011 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)","raw_type":"proceedings-article"},{"id":"pmh:oai:CiteSeerX.psu:10.1.1.229.2","is_oa":false,"landing_page_url":"http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.229.2","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"http://ttic.uchicago.edu/%7Ejkeshet/papers/KeshetMcHa10.pdf","raw_type":"text"}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Reduced inequalities","id":"https://metadata.un.org/sdg/10","score":0.7300000190734863}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":28,"referenced_works":["https://openalex.org/W81836371","https://openalex.org/W128467325","https://openalex.org/W1559312645","https://openalex.org/W1560013842","https://openalex.org/W1607832978","https://openalex.org/W1877570817","https://openalex.org/W2005754897","https://openalex.org/W2032210463","https://openalex.org/W2064082346","https://openalex.org/W2077804127","https://openalex.org/W2083393647","https://openalex.org/W2100474170","https://openalex.org/W2105644991","https://openalex.org/W2105842272","https://openalex.org/W2125534887","https://openalex.org/W2131646590","https://openalex.org/W2133924365","https://openalex.org/W2147880316","https://openalex.org/W2150907703","https://openalex.org/W2158289097","https://openalex.org/W2160218441","https://openalex.org/W3009009611","https://openalex.org/W3149335959","https://openalex.org/W6675760969","https://openalex.org/W6675783020","https://openalex.org/W6679358956","https://openalex.org/W6682082992","https://openalex.org/W6683584131"],"related_works":["https://openalex.org/W2994894110","https://openalex.org/W4377862891","https://openalex.org/W2162582511","https://openalex.org/W4206903459","https://openalex.org/W2005708641","https://openalex.org/W2754816816","https://openalex.org/W4366280654","https://openalex.org/W3160167280","https://openalex.org/W4362706668","https://openalex.org/W4231621013"],"abstract_inverted_index":{"We":[0,33],"describe":[1],"a":[2,27,35],"new":[3],"approach":[4],"for":[5],"phoneme":[6,13,24,46,54,97],"recognition":[7],"which":[8,39],"aims":[9],"at":[10],"minimizing":[11,70],"the":[12,23,44,52,63,66,87,95,108],"error":[14,47,55,98],"rate.":[15,56],"Building":[16],"on":[17,43,86],"structured":[18],"prediction":[19],"techniques,":[20],"we":[21],"formulate":[22],"recognizer":[25],"as":[26],"linear":[28],"combination":[29],"of":[30,51,65],"feature":[31],"functions.":[32],"state":[34],"PAC-Bayesian":[36,67],"generalization":[37],"bound,":[38],"gives":[40],"an":[41],"upper-bound":[42],"expected":[45],"rate":[48,99],"in":[49],"terms":[50],"empirical":[53],"Our":[57],"algorithm":[58,78],"is":[59,79],"derived":[60],"by":[61,72],"finding":[62],"gradient":[64,74],"bound":[68],"and":[69,81,104],"it":[71],"stochastic":[73],"descent.":[75],"The":[76],"resulting":[77],"iterative":[80],"easy":[82],"to":[83,101],"implement.":[84],"Experiments":[85],"TIMIT":[88],"corpus":[89],"show":[90],"that":[91],"our":[92],"method":[93],"achieves":[94],"lowest":[96],"compared":[100],"other":[102],"discriminative":[103],"generative":[105],"models":[106],"with":[107],"same":[109],"expressive":[110],"power.":[111]},"counts_by_year":[{"year":2024,"cited_by_count":2},{"year":2019,"cited_by_count":2},{"year":2018,"cited_by_count":1},{"year":2017,"cited_by_count":2},{"year":2016,"cited_by_count":4},{"year":2015,"cited_by_count":6},{"year":2014,"cited_by_count":6},{"year":2013,"cited_by_count":3},{"year":2012,"cited_by_count":4}],"updated_date":"2026-04-05T17:49:38.594831","created_date":"2025-10-10T00:00:00"}