Towards the detection and description of textual meaning indicators in spontaneous conversations

The description of textual and stylistic features has so far been largely neglected in the empirical study of conversational speech. In this paper we want to make a couple of strong initial points towards the use textual meaning and stylistic features in language engineering: First of all we want to show that there are other besides the traditional features in spontaneous speech that are worth studying and that might reveal good information: These are related to the interactive nature of the language and to the distribution of the most frequent (non-topical) words. Secondly we want to present two tasks that we have chosen as our benchmark and present detection results. Finally we want to motivate how this can be used in information access applications.