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- W2548872034 abstract "In this paper we develop a system for detection of word-related head movements in audiovisu-al recordings of read news. Our materials consist of Swedish television news broadcasts and comprise audiovisual recordings of five news readers (two female, three male). The corpus was manually labelled for head movement, applying a simplistic annotation scheme consisting of a binary decision about absence/presence of a movement in relation to a word. We use OpenCV for frontal face detection and based on this we calculate velocity and acceleration features. Then we train a machine learning system to predict absence or presence of head movement and achieve an accuracy of 0.892, which is better than the baseline. The system may thus be helpful for head movement labelling. (Less)" @default.
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- W2548872034 date "2017-09-25" @default.
- W2548872034 modified "2023-10-04" @default.
- W2548872034 title "Towards classification of head movements in audiovisual recordings of read news" @default.
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