Abstract
To understand a speaker's turn of a conversation, one needs to segment it into intonational phrases, clean up any speech repairs that might have occurred, and identify discourse markers. In this paper, we argue that these problems must be resolved together, and that they must be resolved early in the processing stream. We put forward a statistical language model that resolves these problems, does POS tagging, and can be used as the language model of a speech recognizer. We find that by accounting for the interactions between these tasks that the performance on each task improves, as does POS tagging and perplexity.
| Original language | English (US) |
|---|---|
| Pages (from-to) | 254-261 |
| Number of pages | 8 |
| Journal | Proceedings of the Annual Meeting of the Association for Computational Linguistics |
| Volume | 1997-July |
| State | Published - 1997 |
| Event | 35th Annual Meeting of the Association for Computational Linguistics, ACL 1997 and 8th Conference of the European Chapter of the Association for Computational Linguistics, EACL 1997 - Madrid, Spain Duration: Jul 7 1997 → Jul 12 1997 |
ASJC Scopus subject areas
- Computer Science Applications
- Linguistics and Language
- Language and Linguistics