Retrieving spoken documents by combining multiple index sources

Abstract

This paper presents domain-independent methods of spoken document retrieval. Both a continuous-speech large vocabulary recognition system, and a phone-lattice word spotter, are used to locate index units within an experimental corpus of voice messages. Possible index terms are nearly unconstrained; terms not in a 20,000 word recognition system vocabulary can be identified by the word spotter at search time. Though either system alone can yield respectable retrieval performance, the two methods are complementary and work best in combination. Different ways of combining them are investigated, and it is shown that the best of these can increase retrieval average precision for a speaker-independent retrieval system to 85% of that achieved for full-text transcriptions of the test documents.