%Aigaion2 BibTeX export from Idiap Publications
%Thursday 04 December 2025 06:21:11 PM

@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},
}