The goal of the Video Mail Retrieval (VMR) project is to integrate state-of-the-art information retrieval (IR) methods with high-accuracy word spotting to yield a robust and efficient multimedia retrieval system. This paper concerns op en-talker and arbitrary-keyword retrieval based on talker-independent subword models. Because talker-independent subword models can not be expected to work as well as the talker-dependent whole-keyword models used in previous VMR experiments, speaker adaptation is investigated as a means of improving performance (especially for talkers with non-British accents). Both standard FOM word spotting measures and actual retrieval results are computed. The results show that the FOM is not necessarily a good indicator of retrieval performance, and that talker adaptation can substantially improve both spotting and retrieval results.