{"id":"https://openalex.org/W4392298685","doi":null,"title":"Performance prediction of Automatic Speech Recognition systems","display_name":"Performance prediction of Automatic Speech Recognition systems","publication_year":2019,"publication_date":"2019-03-18","ids":{"openalex":"https://openalex.org/W4392298685"},"language":"fr","primary_location":{"id":"pmh:2019GREAM005","doi":null,"is_oa":true,"landing_page_url":"http://www.theses.fr/2019GREAM005/document","pdf_url":null,"source":{"id":"https://openalex.org/S4406923047","display_name":"theses.fr (ABES)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"repository"},"license":"other-oa","license_id":"https://openalex.org/licenses/other-oa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"Electronic Thesis or Dissertation"},"volume":null,"type":"dissertation","indexed_in":[],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"http://www.theses.fr/2019GREAM005/document","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5063807101","display_name":"Zied Elloumi","orcid":null,"observed_orcids":[]},"institutions":[{"id":"https://openalex.org/I124158823","display_name":"Conservatoire National des Arts et M\u00e9tiers","ror":"https://ror.org/0175hh227","country_code":"FR","type":"education","lineage":["https://openalex.org/I124158823","https://openalex.org/I4210134562"]},{"id":"https://openalex.org/I4210104430","display_name":"Laboratoire d'Informatique de Grenoble","ror":"https://ror.org/01c8rcg82","country_code":"FR","type":"facility","lineage":["https://openalex.org/I106785703","https://openalex.org/I1294671590","https://openalex.org/I1326498283","https://openalex.org/I4210104430","https://openalex.org/I4210159245","https://openalex.org/I899635006"]},{"id":"https://openalex.org/I4405258865","display_name":"Laboratoire commun de m\u00e9trologie","ror":"https://ror.org/01atqpz53","country_code":"FR","type":"facility","lineage":["https://openalex.org/I124158823","https://openalex.org/I4210107682","https://openalex.org/I4210134562","https://openalex.org/I4405258865"]}],"countries":["FR"],"is_corresponding":true,"raw_author_name":"Elloumi, Zied","raw_affiliation_strings":["Laboratoire commun de m\u00e9trologie LNE-CNAM","Laboratoire d'Informatique de Grenoble"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Laboratoire commun de m\u00e9trologie LNE-CNAM","institution_ids":["https://openalex.org/I124158823","https://openalex.org/I4405258865"]},{"raw_affiliation_string":"Laboratoire d'Informatique de Grenoble","institution_ids":["https://openalex.org/I4210104430"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5063807101"],"corresponding_institution_ids":["https://openalex.org/I124158823","https://openalex.org/I4210104430","https://openalex.org/I4405258865"],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":null,"last_page":null},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10201","display_name":"Speech Recognition and Synthesis","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"}},"topics":[{"id":"https://openalex.org/T10201","display_name":"Speech Recognition and Synthesis","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"}},{"id":"https://openalex.org/T10860","display_name":"Speech and Audio Processing","score":9.999999747378752e-05,"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/T12031","display_name":"Speech and dialogue systems","score":0.0,"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/performance-prediction","display_name":"performance prediction","score":0.8140000104904175},{"id":"https://openalex.org/keywords/speech-recognition","display_name":"speech recognition","score":0.984000027179718},{"id":"https://openalex.org/keywords/convolutional-neural-networks","display_name":"convolutional neural networks","score":0.8080000281333923},{"id":"https://openalex.org/keywords/acoustic-characteristics","display_name":"acoustic features","score":0.5389999747276306},{"id":"https://openalex.org/keywords/textual-features","display_name":"text features","score":0.6010000109672546},{"id":"https://openalex.org/keywords/speaker-style","display_name":"speaker style","score":0.4560000002384186},{"id":"https://openalex.org/keywords/speaker-accent","display_name":"speaker accent","score":0.7770000100135803},{"id":"https://openalex.org/keywords/short-utterances","display_name":"short utterances","score":0.6439999938011169},{"id":"https://openalex.org/keywords/multi-task-learning","display_name":"multi-task learning","score":0.703000009059906},{"id":"https://openalex.org/keywords/transfer-learning","display_name":"transfer learning","score":0.3529999852180481},{"id":"https://openalex.org/keywords/robustness","display_name":"robustness","score":0.35199999809265137}],"concepts":[{"id":"https://openalex.org/C28490314","wikidata":"https://www.wikidata.org/wiki/Q189436","display_name":"Speech recognition","level":1,"score":0.7099388837814331},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5685322880744934},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.3904472589492798}],"mesh":[],"locations_count":1,"locations":[{"id":"pmh:2019GREAM005","doi":null,"is_oa":true,"landing_page_url":"http://www.theses.fr/2019GREAM005/document","pdf_url":null,"source":{"id":"https://openalex.org/S4406923047","display_name":"theses.fr (ABES)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"repository"},"license":"other-oa","license_id":"https://openalex.org/licenses/other-oa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"Electronic Thesis or Dissertation"}],"best_oa_location":{"id":"pmh:2019GREAM005","doi":null,"is_oa":true,"landing_page_url":"http://www.theses.fr/2019GREAM005/document","pdf_url":null,"source":{"id":"https://openalex.org/S4406923047","display_name":"theses.fr (ABES)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"repository"},"license":"other-oa","license_id":"https://openalex.org/licenses/other-oa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"Electronic Thesis or Dissertation"},"sustainable_development_goals":[],"study_designs":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":["https://openalex.org/W2924950811","https://openalex.org/W2938437648","https://openalex.org/W2805764708","https://openalex.org/W4392352983","https://openalex.org/W7214256529","https://openalex.org/W7061297258","https://openalex.org/W3088881063","https://openalex.org/W2805833699","https://openalex.org/W91185669","https://openalex.org/W4225658332"],"abstract_inverted_index":{"Nous":[0,142,183],"abordons":[1],"dans":[2,285],"cette":[3,308],"th\u00e8se":[4],"la":[5,17,26,38,82,150,171,188,197,214,235,295,322],"t\u00e2che":[6,22,236,323],"de":[7,9,13,16,29,35,40,70,72,78,86,92,98,117,124,127,130,135,163,170,181,187,193,207,220,229,237,245,253,258,263,294,307,324,326],"pr\u00e9diction":[8,71,194,230,238,325],"performances":[10,73],"des":[11,68,76,105,111,152,175,191,199,243],"syst\u00e8mes":[12,69,77,192,200],"reconnaissance":[14],"automatique":[15],"parole":[18,246,254,259],"(SRAP).Il":[19],"s'agit":[20],"d'une":[21,32],"utile":[23],"pour":[24,64,212],"mesurer":[25],"fiabilit\u00e9":[27],"d'hypoth\u00e8ses":[28],"transcription":[30,39],"issues":[31],"nouvelle":[33,101,218],"collection":[34,157,219],"donn\u00e9es,":[36],"lorsque":[37],"r\u00e9f\u00e9rence":[41],"est":[42,49,239],"indisponible":[43],"et":[44,66,120,210,233,273],"que":[45,75,145,196,225,234,249,281,301],"le":[46,286,292,302],"SRAP":[47],"utilis\u00e9":[48],"inconnu":[50],"(bo\u00eete":[51],"noire).Notre":[52],"contribution":[53],"porte":[54],"sur":[55,95,104,155,216,242,250,291,321],"plusieurs":[56],"axes:d'abord,":[57],"nous":[58,173,261,310],"proposons":[59,311],"un":[60,256,312],"corpus":[61],"fran\u00e7ais":[62],"h\u00e9t\u00e9rog\u00e8ne":[63],"apprendre":[65],"\u00e9valuer":[67],"ainsi":[74,195,248,300],"RAP.Nous":[79],"comparons":[80],"par":[81,269],"suite":[83],"deux":[84,179,227],"approches":[85,180,228],"pr\u00e9diction:":[87],"une":[88,100,156,167,217],"approche":[89,102],"\u00e0":[90,109,160],"l'\u00e9tat":[91],"l'art":[93,164],"bas\u00e9e":[94,103],"l'extraction":[96],"explicite":[97],"traitset":[99],"caract\u00e9ristiques":[106],"entra\u00een\u00e9es":[107],"implicitement":[108],"l'aide":[110],"r\u00e9seaux":[112],"neuronaux":[113],"convolutifs":[114],"(CNN).L'utilisation":[115],"jointe":[116],"traits":[118],"textuels":[119],"acoustiques":[121],"n'apporte":[122],"pas":[123],"gains":[125],"avec":[126,202,276],"l'approche":[128,161],"\u00e9tat":[129,162],"l'art,tandis":[131],"qu'elle":[132],"permet":[133],"d'obtenir":[134],"meilleures":[136],"pr\u00e9dictions":[137],"en":[138],"utilisant":[139],"les":[140,146,178,203,226,251,282],"CNNs.":[141],"montrons":[143],"\u00e9galement":[144,185],"CNNs":[147],"pr\u00e9disent":[148],"clairement":[149],"distribution":[151,168],"taux":[153],"d'erreurs":[154],"d'enregistrements,":[158],"contrairement":[159],"qui":[165,315],"g\u00e9n\u00e8re":[166],"\u00e9loign\u00e9e":[169],"r\u00e9alit\u00e9.Ensuite,":[172],"analysons":[174],"facteurs":[176],"impactant":[177],"pr\u00e9diction.":[182],"\u00e9valuons":[184],"l'impact":[186],"quantit\u00e9":[189],"d'apprentissage":[190],"robustesse":[198],"appris":[201],"sorties":[204],"d'un":[205],"syst\u00e8me":[206,313],"RAP":[208],"particulier":[209],"utilis\u00e9s":[211],"pr\u00e9dire":[213],"performance":[215],"donn\u00e9es.Nos":[221],"r\u00e9sultats":[222],"exp\u00e9rimentaux":[223],"montrent":[224,280],"sont":[231,267],"robustes":[232],"plus":[240,319],"difficile":[241],"tours":[244,252],"courts":[247],"ayant":[255],"style":[257,293],"spontan\u00e9.Enfin,":[260],"essayons":[262],"comprendre":[264],"quelles":[265],"informations":[266,290],"captur\u00e9es":[268],"notre":[270],"mod\u00e8le":[271],"neuronal":[272],"leurs":[274],"liens":[275],"diff\u00e9rents":[277],"facteurs.Nos":[278],"exp\u00e9riences":[279],"repr\u00e9sentations":[283],"interm\u00e9diaires":[284],"r\u00e9seau":[287],"encodent":[288],"implicitementdes":[289],"parole,":[296],"l'accent":[297],"du":[298],"locuteur":[299],"type":[303],"d'\u00e9mission.Pour":[304],"tirer":[305],"profit":[306],"analyse,":[309],"multi-t\u00e2che":[314],"se":[316],"montre":[317],"l\u00e9g\u00e8rement":[318],"efficace":[320],"performance.":[327]},"counts_by_year":[],"updated_date":"2026-09-21T07:43:02.447757","created_date":"2024-03-05T00:00:00"}
