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In this paper, we attempt to quantify the amount of labeled data necessary to build a state-of-the-art speaker recognition system. We begin by using i-vectors and the cosine similarity metric to repre...
This paper investigates the problem of speaker identification and verification in noisy conditions, assuming that speech signals are corrupted by environmental noise, but knowledge about the noise cha...
We provide a supervised speech-independent voice recognition technique in this paper. In the feature extraction stage we propose a mel-cepstral based approach. Our feature vector classification met...

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