This paper presents the second participation of the University of Ottawa group in the Cross-Language Speech Retrieval (CL-SR) task at CLEF 2006. We present the results of the submitted runs for the English collection and very briefly for the Czech collection, followed by many additional experiments. We have used two Information Retrieval systems in our experiments: SMART and Terrier, with several query expansion techniques (including a new method based on log-likelihood scores for collocations). Our experiments showed that query expansion methods do not help much for this collection. We tested different Automatic Speech Recognition transcripts and combinations. The retrieval results did not improve, probably because the speech recognition errors happened for the words that are important in retrieval. We present cross-language experiments, where the queries are automatically translated by combining the results of several online machine translation tools. Our experiments showed that high quality automatic translations (for French) led to results comparable with monolingual English, while the performance decreased for the other languages. Experiments on indexing the manual summaries and keywords gave the best retrieval results.
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