The field of speech processing has undergone a transformative shift with the advent of deep
learning. The use of multiple processing layers has enabled the creation of models capable …

This paper gives an overview of automatic speaker recognition technology, with an
emphasis on text-independent recognition. Speaker recognition has been studied actively …

Support Vector Machines (SVMs) have been one of the most successful machine learning
techniques for the past decade. For anomaly detection, also a semi-supervised variant, the …

This paper extends the within-class covariance normalization (WCCN) technique described
in [1, 2] for training generalized linear kernels. We describe a practical procedure for …

We describe a novel approach to modeling idiosyncratic prosodic behavior for automatic
speaker recognition. The approach computes various duration, pitch, and energy features …

Speaker recognition for different languages is still a big challenge for researchers. The
accuracy of identification rate (IR) is great issue, if the utterance of speech sample is less …

One of the major remaining challenges to improving accuracy in state-of-the-art speaker
recognition algorithms is reducing the impact of channel and handset variations on system …

The paralinguistic information in a speech signal includes clues to the geographical and
social background of the speaker. This paper is concerned with automatic extraction of this …

The speaker recognition has been one of the interesting issues in signal and speech
processing over the last few decades. Feature selection is one of the main parts of speaker …

Задача распознавания диктора по его голосу была поставлена более 40 лет тому
назад, и исследования в этой области все еще продолжаются. Решение этой задачи …