Research on speech processing has traditionally considered the task of designing hand-
engineered acoustic features (feature engineering) as a separate distinct problem from the …

Voice interfaces are becoming accepted widely as input methods for a diverse set of
devices. This development is driven by rapid improvements in automatic speech recognition …

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 analyses the performance of different types of Deep Neural Networks to jointly
estimate age and identify gender from speech, to be applied in Interactive Voice Response …

This paper presents an improved deep embedding learning method based on convolutional
neural networks (CNN) for short-duration speaker verification (SV). Existing deep learning …

Even though speaker recognition has gained significant progress in recent years, its
performance is known to be deteriorated severely with the existence of strong background …

There are a number of studies about extraction of bottleneck (BN) features from deep neural
networks (DNNs) trained to discriminate speakers, pass-phrases, and triphone states for …

This paper deals with joint gender identification and age group classification from speech,
aimed at improving the functionalities of Interactive Voice Response Systems. Deep Neural …

Automatic detection of gender based on audio is gaining its popularity day-by-day because
of its several applications in several domains. But most of the past research works are …

This paper proposes a new loss function called the “quartet” loss for the better optimization
of the neural networks for matching tasks. For such tasks, where neural network embeddings …