The SPRACH/LaSIE system for named entity identification in broadcast news.

Abstract

We have developed two conceptually different systems that are able to identify named entities from spoken audio. One (referred to as SPRACH-S) has a stochastic finite state machine structure for use with an acoustic model that identifies both words and named entities from speech data. The other (referred to as SPRACH-R) is a rule-based system which uses matching against stored name lists, part-of-speech tagging, and light phrasal parsing with specialised named entity grammars. We provide an overview of the two approaches and present results on the Hub-4E IE-NE evaluation task.