Confidence based multimodal fusion for person identification
Philipp W. L. Große, Hartwig Holzapfel, Alex Waibel · 2008
Person identification is of great interest for various kinds of applications and interactive systems. In our system we use face recognition and voice recognition from data recorded in an interactive dialogue system. In such a system, sequential images and sequential utterances can be used to improve recognition accuracy over single hypotheses. The presented approach uses confidence-based fusion for sequence hypotheses, for multimodal fusion, and to provide a reliability measure of the classification quality that can be used to decide when to trust and when to ignore classification results.