Lip-reading technology has the advantage that it can be used even in noisy environments and has been actively studied in recent years. In this paper, we develop a navigation application, "KuchiNavi," as a new application using lip-reading technology. The basic technology is word-level lip-reading technology, which utilizes an existing deep-learning model. However, we quantitatively evaluated lip-reading accuracy by selecting words for navigation, collecting utterance scenes independently, building an original dataset, and conducting recognition experiments. This paper, 101 Japanese words were selected, utterance scenes were collected from 15 people, and recognition experiments were conducted using the speakerindependent recognition task, the leave-one-person-out method. As a result, an average recognition rate of 88.2% was obtained. In addition, we developed an iOS app and conducted a demonstration in a car to confirm its effectiveness.
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