Merging search spaces for subword spoken term detection

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 fuzzysearch 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 3% absolute compared to the edit-distance method.