Speaker Identification (SI) is the process of identifying the speaker from a given utterance by
comparing the voice biometrics of the utterance with those utterance models stored …

Emotion recognition datasets are relatively small, making the use of the more sophisticated
deep learning approaches challenging. In this work, we propose a transfer learning method …

Speaker recognition algorithms are negatively impacted by the quality of the input speech
signal. In this work, we approach the problem of speaker recognition from severely …

The performance of speaker-related systems usually degrades heavily in practical
applications largely due to the presence of background noise. To improve the robustness of …

This paper aims at recognizing emotions for a text-independent and speaker-independent
emotion recognition system based on a novel classifier, which is a hybrid of a cascaded …

This work aims at intensifying text-independent speaker identification performance in real
application situations such as noisy and emotional talking conditions. This is achieved by …

Language recognition systems based on bottleneck features have recently become the state-
of-the-art in this research field, showing its success in the last Language Recognition …

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 …

This research is an effort to present an effective approach to enhance text-independent
speaker identification performance in emotional talking environments based on novel …

In this work, we present an analysis of a DNN-based autoencoder for speech enhancement,
dereverberation and denoising. The target application is a robust speaker verification (SV) …