INTERSPEECH 2009
10th Annual Conference of the International Speech Communication Association

Brighton, United Kingdom
September 6-10, 2009

A Posterior Probability-Based System Hybridisation and Combination for Spoken Term Detection

Javier Tejedor (1), Dong Wang (2), Simon King (2), Joe Frankel (2), José Colás (1)

(1) Universidad Autónoma de Madrid, Spain
(2) University of Edinburgh, UK

Spoken term detection (STD) is a fundamental task for multimedia information retrieval. To improve the detection performance, we have presented a direct posterior-based confidence measure generated from a neural network. In this paper, we propose a detection-independent confidence estimation based on the direct posterior confidence measure, in which the decision making is totally separated from the term detection. Based on this idea, we first present a hybrid system which conducts the term detection and confidence estimation based on different sub-word units and then propose a combination method which merges detections from heterogeneous term detectors based on the direct posterior-based confidence. Experimental results demonstrated that the proposed methods improved system performance considerably for both English and Spanish.

Full Paper

Bibliographic reference.  Tejedor, Javier / Wang, Dong / King, Simon / Frankel, Joe / Colás, José (2009): "A posterior probability-based system hybridisation and combination for spoken term detection", In INTERSPEECH-2009, 2131-2134.