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This paper addresses the adaptation of an acoustic-articulatory inversion model of a reference speaker to the voice of another source speaker, using a limited amount of audio-only data. In this study, the articulatory-acoustic relationship of the reference speaker is modeled by a Gaussian mixture model and inference of articulatory data from acoustic data is made by the associated Gaussian mixture...
Gaussian Mixture Model (GMM) is a widely used, simple and effective modeling approach for spoken language identification. Traditionally EM algorithm is used to train this model. In this paper we propose a new method named WA-GMM (Weight Adapted GMM) for estimating the weights of GMM Gaussian components using bag-of-unigram and Support Vector Machine (SVM): SVM weights which are trained on bag-of-unigram...
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