REPORT grangier:2007:rr_07-15/IDIAP Learning the Inter-frame Distance for Discriminative Template-based Keyword Detection Grangier, David Bengio, Samy EXTERNAL https://publications.idiap.ch/attachments/reports/2007/grangier_rr_07-15.pdf PUBLIC Idiap-RR-15-2007 2007 IDIAP 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.