%Aigaion2 BibTeX export from Idiap Publications
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@TECHREPORT{grangier:2007:rr_07-15,
         author = {Grangier, David and Bengio, Samy},
       projects = {Idiap},
          title = {Learning the Inter-frame Distance for Discriminative Template-based Keyword Detection},
           type = {Idiap-RR},
         number = {Idiap-RR-15-2007},
           year = {2007},
    institution = {IDIAP},
       abstract = {This paper proposes a discriminative approach to template-based keyword detection. We introduce a method to learn the distance used to compare acoustic frames, a crucial element for template matching approaches. The proposed algorithm estimates the distance from data, with the objective to produce a detector maximizing the Area Under the receiver operating Curve (AUC,',','),
 i.e. the standard evaluation measure for the keyword detection problem. The experiments performed over a large corpus, SpeechDatII, suggest that our model is effective compared to an HMM system, e.g. the proposed approach reaches 93.8\\% of averaged AUC compared to 87.9\\% for the HMM.},
            pdf = {https://publications.idiap.ch/attachments/reports/2007/grangier_rr_07-15.pdf},
     postscript = {ftp://ftp.idiap.ch/pub/reports/2007/grangier_rr_07-15.ps.gz},
ipdmembership={learning},
}