Discriminative word-spotting using ordered spectro-temporal patch features.
Tony Ezzat, Tomaso Poggio · 2008
We present a novel architecture for word-spotting which is trained from a small number of examples to classify an utterance as containing a target keyword or not. The word-spotting architecture relies on a novel feature set consisting of a set of ordered spectro-temporal patches which are extracted from exemplar mel-spectra of target keywords. A local pooling operation across frequency and time is introduced which endows the extracted patch features with the flexibility to match novel