We present a framework where auxiliary MT systems are used to provide lexical predictions to a main SMT system. In this work, predictions are obtained by means of pivoting via aux...
This paper proposes an efficient online method that trains a classifier with many conjunctive features. We employ kernel computation called kernel slicing, which explicitly consid...
This paper proposes a new approach to phrase rescoring for statistical machine translation (SMT). A set of novel features capturing the translingual equivalence between a source a...
—In this paper, we investigate the source–filter-based approach for single-channel speech separation. We incorporate source-driven aspects by multi-pitch estimation in the mod...
This paper presents a novel methodology to infer parameters of probabilistic models whose output noise is a Student-t distribution. The method is an extension of earlier work for ...