This paper deals with the problem of processing of I-vectors in the text-independent speaker
verification systems. A new generalized cosine similarity optimization technique is proposed …

Abstract Cosine similarity and Probabilistic Linear Discriminant Analysis (PLDA) in i-vector
space are two state-of-the-art scoring methods in speaker verification field. While PLDA …

Factor analysis is mainly by extracting the compact representations of speakers' utterances,
which are referred to as i-vectors. A low new space called total variability space, which is …

In this article the text-independent speaker verification problem is considered. In the
presented system each conversation side is represented as a vector lying on the unit …

Over recent years, i-vector-based framework has been proven to provide state-of-the-art
performance in speaker verification. Each utterance is projected onto a total factor space …

In the recent years, design of robust and effective speaker verification algorithms has
attracted significant research effort from academic and commercial institutions. Speaker …

Over recent years, i-vector based framework has been proven to provide state-of-art
performance in speaker verification. Most of the researches focus on compensating the …

In this paper, we propose a new method for concurrent accuracy and computational
efficiency optimization using a fuzzy clusters tree for i-vector speaker identification. The …

The identity vector (i‐vector) approach has been the state‐of‐the‐art for text‐independent
speaker recognition, both identification and verification in recent years. An i‐vector is a low …

In this article a text-independent speaker verification problem is considered. After the feature
extraction, each conversation side has been represented as a vector in a fixed dimensional …