Confidence-Weighted linear classifiers (CW) and its successors were shown to perform well on binary and multiclass NLP problems. In this paper we extend the CW approach for sequen...
Commonly used speech enhancement algorithms estimate the power spectral density of the noise to be removed, or make a decision about the presence of speech in a particular frame, ...
Labeled data for classification could often be obtained by sampling that restricts or favors choice of certain classes. A classifier trained using such data will be biased, resulti...
An important aspect in the development of dependable software is to decide where to locate mechanisms for efficient error detection and recovery. We present a comparison between ...
Artificial neural networks (ANN's) are associated with difficulties like lack of success in a given problem and unpredictable level of accuracy that could be achieved. In eve...