This paper presents an unsupervised segment-based method for robust voice activity
detection (rVAD). The method consists of two passes of denoising followed by a voice …

Effective speech activity detection (SAD) is a necessary first step for robust speech
applications. In this letter, we propose a robust and unsupervised SAD solution that …

Voice activity detection (VAD) is an important topic in audio signal processing. Contextual
information is important for improving the performance of VAD at low signal-to-noise ratios …

Convolutional neural networks (CNN) are extensions to deep neural networks (DNN) which
are used as alternate acoustic models with state-of-the-art performances for speech …

This paper describes the speech activity detection (SAD) system developed by the Patrol
team for the first phase of the DARPA RATS (Robust Automatic Transcription of Speech) …

This paper compares different approaches for using deep neural networks (DNNs) trained to
predict senone posteriors for the task of spoken language recognition (SLR). These …

Following recent advancements in deep learning and artificial intelligence, spoken
language identification applications are playing an increasingly significant role in our day-to …

As has been extensively shown, acoustic features for speech recognition can be learned
from neural networks with multiple hidden layers. However, the learned transformations may …

A phoneme is the smallest perceptually distinct sound unit that can be distinguished among
words in a particular language. Every language has its own set of phonemes, and all …

With the recent introduction of speaker embeddings for text-independent speaker
recognition, many fundamental questions require addressing in order to fast-track the …