We present a novel paradigm for statistical machine translation (SMT), based on a joint modeling of word alignment and the topical aspects underlying bilingual document-pairs, via...
We propose a non-linear Canonical Correlation Analysis (CCA) method which works by coordinating or aligning mixtures of linear models. In the same way that CCA extends the idea of...
In this paper we present a family of models and learning algorithms that can simultaneously align and cluster sets of multidimensional curves measured on a discrete time grid. Our...
We consider the multi-class classification problem, based on vector observation sequences, where the conditional (given class observations) probability distributions for each class...
This paper proposes a method for separating the signals of individual musical instruments from monaural musical audio. The mixture signal is modeled as a sum of the spectra of ind...