Cross-Language Spoken Document Retrieval (CLSDR) combines both the complexities of retrieval from collections characterized by speech transcription errors and language translation issues between search requests and documents. Thus achieving effective retrieval in this domain is potentially very challenging. For the CLEF 2003 SDR task we adopted a standard query translation strategy using commercial machine translation tools and explored pseudo-relevance feedback using a small contemporaneous collection and a much larger text collection from a different time period.