Paper: Named Entity Scoring for Speech Input

ACL ID P98-1031
Title Named Entity Scoring for Speech Input
Venue Annual Meeting of the Association of Computational Linguistics
Session Main Conference
Year 1998

This paper describes a new scoring algorithm that supports comparison of linguistically annotated data from noisy sources. The new algorithm generalizes the Message Understanding Conference (MUC) Named Entity scoring algorithm, using a compari- son based on explicit alignment of the underlying texts, followed by a scoring phase. The scoring procedure maps corresponding tagged regions and compares these according to tag type and tag extent, allowing us to reproduce the MUC Named Entity scoring for identical underlying texts. In addition, the new algorithm scores for content (transcription correctness) of the tagged region, a useful distinc- tion when dealing with noisy data that may differ from a reference transcription (e.g. , speech recog- nizer output). To illustrate the algorithm, we ha...