4 accepted papers
A speaker verification system decides whether two voice segments belong to the same speaker based on a threshold. An optimal threshold can be set if the recognition scores are well calibrated, i.e., they represent Log-Likelihood Ratios. Logistic Regression (LogReg) is a standard approach for score c…
Systems based on i-vectors represent the current state-of-the-art in text-independent speaker recognition. In this work we introduce a new compact representation of a speech segment, similar to the speaker factors of Joint Factor Analysis (JFA) and to i-vectors, that we call “e-vector”. The e-vector…
Domain mismatch occurs when data from application-specific target domain is related to, but cannot be viewed as iid samples from the source domain used for training speaker models. Another problem occurs when several training datasets are available but their domains differ. In this case training on…
Most of the state-of-the-art speaker recognition systems use i-vectors, a compact representation of spoken utterances. Since the “standard” i-vector extraction procedure requires large memory structures, we recently presented the Factorized Sub-space Estimation (FSE) approach, an efficient technique…