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Exploring Gaps in DeepFool inSearch of More Effective Adversarial Perturbations
Adversarial examples are inputs subtly perturbed to produce a wrong prediction in machine learning models, while remaining perceptually similar to the original input. To find adversarial examples, some attack strategies ...
Analysis of the sensitivity of the End-Of-Turn Detection task to errors generated by the Automatic Speech Recognition process.
An End-Of-Turn Detection Module (EOTD-M) is an essential component of au- tomatic Spoken Dialogue Systems. The capability of correctly detecting whether a user’s utterance has ended or not improves the accuracy in interpreting ...