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Accurate racism classification is crucial on social media, where racist and discriminatory content can harm individuals and society. Automated racism detection requires gathering and annotating a wide range of diverse and representative data as an ...

Deep learning models are now considered state-of-the-art in many areas of pattern recognition. In speaker recognition, several architectures have been studied, such as deep neural networks (DNNs), deep belief networks (DBNs), restricted Boltzmann ...

We propose a novel usage of convolutional neural networks (CNNs) for the problem of speaker recognition. While being particularly designed for computer vision problems, CNNs have recently been applied for speaker recognition by using spectrograms ...

Speaker verification (SV) is an important branch in speaker recognition. Several approaches have been investigated within the last few decades. In this context, deep learning has received much more interest by speech processing researchers, and it ...

Nowadays, stochastic models are state-of-the-art for text-independent speaker verification. However, they are costly in terms of time-consuming and may need much more data in the training phase. This paper proposes a novel scoring method based on ...

Gravier, Guillaume, Kharroubi, Jamal, and Chollet, Gérard, On the Use of Prior Knowledge in Normalization Schemes for Speaker Verification, Digital Signal Processing10(2000), 213 225.Recent research on text-independent speaker verification systems has ...