The limited battery capacity of sensor nodes has become the biggest impediment to wireless
sensor network (WSN) applications. Two recent breakthroughs in the areas of wireless …

The low-dimensional i-vector representation of speech segments is used in the state-of-the-
art text-independent speaker verification systems. However, i-vectors were deemed …

In this paper, we introduce a new database for text-dependent, text-prompted and text-
independent speaker recognition, as well as for speech recognition. DeepMine is a large …

Inspired by the success of Deep Neural Networks (DNN) in text-independent speaker
recognition, we have recently demonstrated that similar ideas can also be applied to the text …

Deep Neural Networks and Hidden Markov Models in i-vector-based Text-Dependent Speaker
Verification Page 1 1/11 Introduction HMM based method Deep Neural Networks (DNNs) …

In the last decade, i-vector and Joint Factor Analysis (JFA) approaches to speaker modeling
have become ubiquitous in the area of automatic speaker recognition. Both of these …

This study proposes depression detection systems based on the i-vector framework for
classifying speakers as depressed or healthy and predicting depression levels according to …

In this paper, we combine Hidden Markov Models (HMMs) with i-vector extractors to address
the problem of text-dependent speaker recognition with random digit strings. We employ …

Signature verification (SV) is one of the common methods for identity verification in banking,
where for security reasons, it is very important to have an accurate method for automatic SV …

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 …