Adaptive utterance rewriting for conversational search

Adaptive search area for fast motion estimation

In this paper a new method for determining the search area for motion estimation algorithm based on block matching is suggested. In the proposed method the search area is adaptively found for each block of a frame. This search area is similar to that of the full search (FS) algorithm but smaller for most blocks of a frame. Therefore, the proposed algorithm is analogous to FS in terms of reg...

Neural Utterance Ranking Model for Conversational Dialogue Systems

In this study, we present our neural utterance ranking (NUR) model, an utterance selection model for conversational dialogue agents. The NUR model ranks candidate utterances with respect to their suitability in relation to a given context using neural networks; in addition, a dialogue system based on the model converses with humans using highly ranked utterances. Specifically, the model process...

Lattice-Based Search for Spoken Utterance Retrieval

Recent work on spoken document retrieval has suggested that it is adequate to take the singlebest output of ASR, and perform text retrieval on this output. This is reasonable enough for the task of retrieving broadcast news stories, where word error rates are relatively low, and the stories are long enough to contain much redundancy. But it is patently not reasonable if one’s task is to retriev...

Challenges for Adaptive Conversational Agents

State-of-the-art dialogue technology has reached a level that allows its use in commercial applications, enabling users to have short conversations with the system to search for information. However, the unique requirements that arise from the combination of system knowledge representation, interaction management, and interface design have to be addressed as part of the system development proce...

Towards Context-adaptive Utterance Interpretation