This paper presents a phone-based approach of spoken document retrieval, developed in the framework of the emerging MPEG-7 standard. The audio part of MPEG-7 encloses a SpokenContent tool that provides a standardized description of the content of spoken documents. In the context of MPEG-7, we propose an indexing and retrieval method that uses phonetic information only and a vector space IR model. Experiments are conducted on a database of German spoken documents, with 10 city name queries. Two phone-based retrieval approaches are presented and combined. The first one is based on the combination of phone N-grams of different lengths used as indexing terms. The other consists of expanding the document representation by means of phone confusion probabilities.
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