Cross-language speech retrieval: Establishing a baseline performance

We present here the realisation of a cross-language speech retrieval system which retrieves German speech documents in response to user queries specified as French text. This has been achieved through the integration of two existing modules of the SPIDER information retrieval system, namely the query pseudo-translation module and the speech retrieval module. Our approach to cross-language retrieval uses an automatically contstructed corpus-based information structure called a similarity thesaurus. A similarity thesaurus can be constructed over any loosely comparable corpus - a parallel corpus is not necessary. The similarity thesaurus used here was constructed over a 330 MByte corpus of comparable German and French news stories. Our speech retrieval module is based on a speaker-independent phoneme recognizer and it indexes speech documents by N-grams of phonemic features. The speech retrieval module includes an additional probabilistic matching technique designed to aid retrieval from erroneous data such as the phonemic output of the speech recognition process. We have evaluated our cross-language speech retrieval system over a collection of 30 hours (3.4 GBytes) of German speech, comparing the effectiveness of French queries (cross-language) against performance on equivalent German queries (mono-lingual). It must be stressed that this work represents our first step in the direction of cross-language speech retrieval. Our aim here is to establish a baseline of performance on this task, against which we can then measure the success of our continuing research in this area.