A major challenge faced by a spoken term detection (STD) system is the detection of out-of-vocabulary (OOV) terms. Although a subword-based STD system is able to detect OOV terms, performance reduction is always observed compared to in-vocabulary terms. Current approaches to STD do not acknowledge the particular properties of OOV terms, such as pronunciation uncertainty. In this paper, we use a stochastic pronunciation model to deal with the uncertain pronunciations of OOV terms. By considering all possible term pronunciations, predicted by a joint-multigram model, we observe a significant performance improvement.
|Title of host publication||Proceedings of Interspeech 2009 Brighton|
|Number of pages||4|
|Publication status||Published - 2009|