11th Annual Conference of the International Speech Communication Association

Makuhari, Chiba, Japan
September 26-30. 2010

Contextual Verification for Open Vocabulary Spoken Term Detection

Daniel Schneider (1), Timo Mertens (2), Martha Larson (3), Joachim Köhler (1)

(1) Fraunhofer IAIS, Germany
(2) NTNU, Norway
(3) Technische Universiteit Delft, The Netherlands

In spoken term detection, subword speech recognition is a viable means for addressing the out-of-vocabulary (OOV) problem at query time. Applying fuzzy error compensation techniques is needed for coping with inevitable recognition errors, but can lead to high false alarm rates especially for short queries. We propose two novel methods which reject false alarms based on the context of the hypothesized result and the distance to phonetically similar queries. Using the proposed methods, we obtain an increase in precision of 11% absolute at equal recall.

Full Paper

Bibliographic reference.  Schneider, Daniel / Mertens, Timo / Larson, Martha / Köhler, Joachim (2010): "Contextual verification for open vocabulary spoken term detection", In INTERSPEECH-2010, 697-700.