This paper investigates adapting a lexicalized probabilistic context-free grammar (PCFG) to a novel domain, using maximum a posteriori (MAP) estimation. The MAP framework is gener...
In this paper, we present a new approach to HMM adaptation that jointly compensates for additive and convolutive acoustic distortion in environment-robust speech recognition. The ...
Jinyu Li, Li Deng, Dong Yu, Yifan Gong, Alex Acero
Over the last years, object detection has become a more and more active field of research in robotics. An important problem in object detection is the need for sufficient labeled ...
Object recognition accuracy can be improved when information from multiple views is integrated, but information in each view can often be highly redundant. We consider the problem...
Chris Mario Christoudias, Raquel Urtasun, Trevor D...
This paper investigates the impact of subspace based techniques for acoustic modeling in automatic speech recognition (ASR). There are many well known approaches to subspace based...