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The paper proposes a kind of visual speech feature for the speaking mouth images from the video combining clues of the shape and local teeth texture. The geometric feature we proposed based on the computing the Euclidian distant between each the feature point around the inner and outer lip. The local texture with G and B components as baseline is employed to calculate the color moment to describe...
In this paper, we propose a self-organized clustering method for feature mapping to compensate the channel variation in spoken language recognition. The self-organized clustering is realized by transforming the utterances into the Gaussian mixture model (GMM) supervectors and categorizing the supervectors through k-mean algorithm. Based on the language-dependent cluster-of-utterance information of...
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