Voice activity detection using an adaptive context attention model
Voice activity detection (VAD) classifies incoming signal segments into speech or
background noise; its performance is crucial in various speech-related applications …
background noise; its performance is crucial in various speech-related applications …
Spectro-temporal attention-based voice activity detection
Voice Activity Detection (VAD) systems suffer from unexpected and non-stationary
background noises at magnitudes sufficiently high to mask the speech signal. Although …
background noises at magnitudes sufficiently high to mask the speech signal. Although …
Robust voice activity detection using an auditory-inspired masked modulation encoder based convolutional attention network
Deep learning has revolutionized voice activity detection (VAD) by offering promising
solutions. However, directly applying traditional features, such as raw waveforms and Mel …
solutions. However, directly applying traditional features, such as raw waveforms and Mel …
Spiking neural networks trained with backpropagation for low power neuromorphic implementation of voice activity detection
Recent advances in Voice Activity Detection (VAD) are driven by artificial and Recurrent
Neural Networks (RNNs), however, using a VAD system in battery-operated devices …
Neural Networks (RNNs), however, using a VAD system in battery-operated devices …
Hardware-optimized reservoir computing system for edge intelligence applications
Edge artificial intelligence or edge intelligence is an ever-growing research area due to the
current popularization of the Internet of Things. Unfortunately, incorporation of artificial …
current popularization of the Internet of Things. Unfortunately, incorporation of artificial …
A voice activity detection algorithm using deep learning in time–frequency domain
S Mavaddati - Neural Computing and Applications, 2024 - Springer
Voice activity detection (VAD) is an important component of signal processing that is critical
for various applications, including speech recognition, speaker recognition, and speaker …
for various applications, including speech recognition, speaker recognition, and speaker …
Efficient speech detection in environmental audio using acoustic recognition and knowledge distillation
The ongoing biodiversity crisis, driven by factors such as land-use change and global
warming, emphasizes the need for effective ecological monitoring methods. Acoustic …
warming, emphasizes the need for effective ecological monitoring methods. Acoustic …
Child-adult speech diarization in naturalistic conditions of preschool classrooms using room-independent ResNet model and automatic speech recognition-based re …
PV Kothalkar, JHL Hansen, D Irvin… - The Journal of the …, 2024 - pubs.aip.org
Speech and language development are early indicators of overall analytical and learning
ability in children. The preschool classroom is a rich language environment for monitoring …
ability in children. The preschool classroom is a rich language environment for monitoring …
A frequency-domain approach with learnable filters for image classification
Abstract Machine learning applied to computer vision and signal processing is achieving
results comparable to the human brain due to the great improvements brought by deep …
results comparable to the human brain due to the great improvements brought by deep …
[PDF][PDF] A Lightweight Framework for Online Voice Activity Detection in the Wild.
Voice activity detection (VAD) is an essential pre-processing component for speech-related
tasks such as automatic speech recognition (ASR). Traditional VAD systems require strong …
tasks such as automatic speech recognition (ASR). Traditional VAD systems require strong …