A robust and language agnostic Voice Activity Detection (VAD) is crucial for Digital
Entertainment Content (DEC). Primary examples of DEC include movies and TV series …

A novel, data-driven approach to voice activity detection is presented. The approach is
based on Long Short-Term Memory Recurrent Neural Networks trained on standard RASTA …

We present a novel recurrent neural network (RNN) model for voice activity detection. Our
multi-layer RNN model, in which nodes compute quadratic polynomials, outperforms a much …

Abstract Voice Activity Detection (VAD) is an important preprocessing step in any state-of-the-
art speech recognition system. Choosing the right set of features and model architecture can …

Voice Activity Detection (VAD) refers to the problem of distinguishing speech segments from
background noise. Numerous approaches have been proposed for this purpose. Some are …

In this article, we address the problem of creating a smart audio guide that adapts to the
actions and interests of museum visitors. As an autonomous agent, our guide perceives the …

Voice activity detection (VAD) in the presence of heavy, nonstationary noise is a challenging
problem that has attracted attention in recent years. Most modern VAD systems require …

Smart homes aim at enhancing the quality of life of people at home by the use of home
automation systems and Ambient Intelligence. Most of these smart homes provide enhanced …

Video of a classroom lecture has been shown to be a versatile learning resource
comparable to a textbook. Captions in videos are highly valued by students, especially those …

We present a novel generative model for audio event transcription that recognizes “events”
on audio signals including multiple kinds of overlap** sounds. In the proposed model …