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The success of the recent i-vector approach to speaker verification relies on the capability of i-vectors to capture speaker characteristics and the subsequent channel compensation methods to suppress channel variability. Typically, given an utterance, an i-vector is determined from the utterance regardless of its length. This paper investigates how the utterance length affects the discriminative...
This paper investigates the small sample-size problem in i-vector based speaker verification systems. The idea of i-vectors is to represent the characteristics of speakers in the factors of a factor analyzer. Because the factor loading matrix defines the possible speakerand channel-variability of i-vectors, it is important to suppress the unwanted channel variability. Linear discriminant analysis...
This paper presents the HKCUPU speaker recognition system submitted to NIST 2010 speaker recognition evaluation (SRE). The system comprises five subsystems, each with different acoustic features, session-variability reduction methods, speaker modeling and scoring methods and classifiers. This paper reports the results of individual and fusion systems for the core test and highlights the improvements...
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