Statistical analysis of dialogue structure
Ye‐Yi Wang, Alex Waibel · 1997
We introduce a statistical model for dialogues. We describe a dynamic programming algorithm that can be used to bracket a dialogue into segments and label each segment with its speech act. We evaluate the performance of the model. We also use this model for language modelling and get perplexity reduction. 1 INTRODUCTION Dialogue structure provides important information for spoken language understanding. This structure comprises the current topic, discourse state, and speech act, etc. Many researchers used topic information to reduce the perplexity of a task [1, 2]. In our experiments, we also found that dialogue structure information also helps to reduce ambiguities and improve spoken language translation performance. While knowledge-based approaches are used widely and successfully in dialogue structure analysis[3, 4], they require intensive human effort in defining linguistic structures and developing grammars to detect the structures. We would like to build a model that is able to ...