Source normalization for language-independent speaker recognition using i-vectors

A PLDA approach for language and text independent speaker recognition

There are many factors affecting the variability of an i-vector extracted from a speech segment such as the acoustic content, segment duration, handset type and background noise. The state-of-the-art Probabilistic Linear Discriminant Analysis (PLDA) aims at modelling all these sources of undesirable variability within a single covariance matrix. Although techniques such as source normalization ...

Content Normalization for Text-independent Speaker Verification

In the past few years, Deep Neural Network (DNN) based ivector Speaker Verification (SV) systems have shown to provide state-of-the-art performance. However, error rates increase drastically for short duration recordings. In this paper, we improve the i-vector approach for short utterances, (i) by using smoothed DNN posteriors for i-vector extraction, and (ii) by normalizing the content of the ...

Connectionist Speaker Normalization and Its Applications to Speech Recognition

Speaker normalization may have a significant impact on both speakeradaptive and speaker-independent speech recognition. In this paper, a codeworddependent neural network (CDNN) is presented for speaker normalization. The network is used as a nonlinear mapping function to transform speech data between two speakers. The mapping function is characterized by two important properties. First, the ass...

Speaker Independent Speech Recognition Using Hidden Markov Models for Persian Isolated Words

Improving short utterance based i-vector speaker recognition using source and utterance-duration normalization techniques

A significant amount of speech is typically required for speaker verification system development and evaluation, especially in the presence of large intersession variability. This paper introduces a source and utterance-duration normalized linear discriminant analysis (SUN-LDA) approaches to compensate session variability in short-utterance i-vector speaker verification systems. Two variations ...