Phonetic confusion based document expansion for spoken document retrieval

Abstract

This paper presents a phone-based approach of spoken document retrieval (SDR), developed in the framework of the emerging MPEG-7 standard. We describe an indexing and retrieval system that uses phonetic information only. The retrieval method is based on the vector space IR model, using phone N-grams as indexing terms. We propose a technique to expand the representation of documents by means of phone confusion probabilities in order to improve the retrieval performance. This method is tested on a collection of short German spoken documents, using 10 city names as queries.