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...
In this paper, we describe a new multi-purpose audio-visual database on the context of speech interfaces for controlling household electronic devices. The database comprises speec...
Spoken Language Understanding (SLU) addresses the problem of extracting semantic meaning conveyed in an utterance. The traditional knowledge-based approach to this problem is very...
In this paper, a new language model, the Multi-Class Composite N-gram, is proposed to avoid a data sparseness problem for spoken language in that it is difficult to collect traini...
While the notion of a cooperative response has been the focus of considerable research in natural language dialogue systems, there has been little empirical work demonstrating how...