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Exemplar based recognition systems are characterized by the fact that, instead of abstracting large amounts of data into compact models , they store the observed data enriched with some annotations and infer on-the-fly from the data by finding those exemplars that resemble the input speech best. One advantage of exemplar based systems is that next to(More)
SPRAAK is a toolkit intended for • Speech recognition research • Development of speech recognition applications (niche markets) Licensing • Free source code license for academic usage (open source concept) • Commercial license Development History • Derived from HMM75 that has a >15 year development history at KULeuven • Modernization & Conversion was(More)
The goal of this workshop group is to advance the state-of-the-art in core speech recognition by developing new kinds of informative segment level features for use in a Segmental Conditional Random Field (SCRF). In the recently proposed SCRF approach [Zweig & Nguyen 2009], we generalize Conditional Random Fields to operate at the segment level, rather than(More)
Speech recognition in adverse conditions remains a difficult but challenging problem. It is already shown [1] that normalisation of the dynamic range (SNR 1) of the frequency channels in a mel scale triangular filterbank (MFCC) [2], improves the robustness against both additive and convolutional noise. Nevertheless, because the method is based on a(More)