The Mel-Frequency Cepstral Coefficients (MFCC) feature extraction method is a leading
approach for speech feature extraction and current research aims to identify performance …

The use of Mel-frequency cepstral coefficients (MFCCs) is well established in the fields of
speech processing, particularly for speaker modeling within a Gaussian mixture model …

In this paper, an information theoretic approach to selecting feature frames for speaker
recognition systems is proposed. A conventional approach in which the frame shift is fixed to …

Recently, we introduced the sorted Gaussian mixture models (SGMMs) algorithm providing
the means to tradeoff performance for operational speed and thus permitting the speed-up of …

In this paper, an adaptive recognition of different accents conversations is proposed based
on Convolutional Neural Network (CNN), which is used to deal with dialogue speech …

In this paper, a new and novel Automatic Speaker Recognition (ASR) system is presented.
The new ASR system includes novel feature extraction and vector classification steps …

In this paper a new inter-frame fast scoring scheme is proposed for Gaussian mixture model
universal background model (GMM-UBM) speaker verification systems. It is combined with a …

In this paper, we propose a hierarchical mixture clustering method and investigate its
application for complexity reduction of a GMM based speaker identification system. We show …

In this paper, a speaker segmentation algorithm is proposed based on a Combined feature
approach using the Convolution Neural Network (CNN), which is used to deal with the …

Aufgrund ihres individuellen, charakteristischen Klangs stellt die menschliche Stimme ein
biometrisches Merkmal dar, das zum Beispiel fur Anwendungen der Authentifizierung …