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Discriminating Unknown Objects from Known Objects Using Image and Speech Information
Yuko OZASA Mikio NAKANO Yasuo ARIKI Naoto IWAHASHI
IEICE TRANSACTIONS on Information and Systems
Publication Date: 2015/03/01
Online ISSN: 1745-1361
Type of Manuscript: PAPER
Category: Multimedia Pattern Processing
multimodality, unknown object discrimination, object recognition, information integration,
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This paper deals with a problem where a robot identifies an object that a human asks it to bring by voice when there is a set of objects that the human and the robot can see. When the robot knows the requested object, it must identify the object and when it does not know the object, it must say it does not. This paper presents a new method for discriminating unknown objects from known objects using object images and human speech. It uses a confidence measure that integrates image recognition confidences and speech recognition confidences based on logistic regression.