Applying compensation techniques on i-vectors extracted from short-test utterances for speaker verification using deep neural network

Abstract

We propose a method to improve speaker verification performance when a test utterance is very short. In some situations with short test utterances, performance of ivector/probabilistic linear discriminant analysis systems degrades. The proposed method transforms short-utterance feature vectors to adequate vectors using a deep neural network, which… (More)
DOI: 10.1109/ICASSP.2017.7953206

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