—Natural human-robot interaction requires different and more robust models of language understanding (NLU) than non-embodied NLU systems. In particular, architectures are require...
Rehj Cantrell, Matthias Scheutz, Paul W. Schermerh...
Abstract. As potential candidates for human cognition, connectionist models of sentence processing must learn to behave systematically by generalizing from a small traning set. It ...
In many settings, such as home care or mobile environments, demands on users' attention, or users' anticipated level of formal training, or other on-site conditions will...
Most previous work on trainable language generation has focused on two paradigms: (a) using a statistical model to rank a set of generated utterances, or (b) using statistics to i...
Data-driven Spoken Language Understanding (SLU) systems need semantically annotated data which are expensive, time consuming and prone to human errors. Active learning has been su...