We describe how complementary search spaces, addressed by two different methods used in Spoken Term Detection (STD), can be merged for German subword STD. We propose fuzzy-search techniques on lattices to narrow the gap between subword and word retrieval. The first technique is based on an edit-distance, where no a priori knowledge about confusions is employed. Additionally, we propose a weighting method which explicitly models pronunciation variation on a subword level and thus improves robustness against false positives. Recall is improved by 6% absolute when retrieving on the merged search space rather than using an exact lattice search. By modeling subword pronunciation variation, we increase recall in a high-precision setting by 2% absolute compared to the edit-distance method.
Bibliographic reference. Mertens, Timo / Schneider, Daniel / Köhler, Joachim (2009): "Merging search spaces for subword spoken term detection", In INTERSPEECH-2009, 2127-2130.