Modelling multimodal user ID in dialogue
Hartwig Holzapfel, Alex Waibel · 2008
This paper presents an approach to model user ID in dialogue. A belief network is used to integrate ID classifiers, such as face ID and voice ID, and person related information, such as the first name and last name of a person from speech recognition or spelling. Different network structures are analyzed and compared with each other and are compared with a rule-based user model. The approach is evaluated on dialogue data collected in a person identification scenario, which includes both, identification of known persons and interactive learning of names and ID of unknown persons.