Enhancing posterior based speech recognition systems
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The goal of this thesis is to improve current state-of-the-art techniques in speaker verification
(SV), typically based on âidentity-vectorsâ (i-vectors) and deep neural network (DNN), by exploiting diverse (phonetic) information extracted using variou ...
In a recent work, we have shown that speaker verification systems can be built where both features and classifiers are directly learned from the raw speech signal with convolutional neural networks (CNNs). In this framework, the training phase also decides ...
