2 citations · 2 across the 3 of their papers we have counts for
4 papers · 1 filter
BC-VAD: A Robust Bone Conduction Voice Activity Detection
Niccolo' Polvani, Damien Ronssin, Milos Cernak
Voice Activity Detection (VAD) is a fundamental module in many audio applications. Recent state-of-the-art VAD systems are often based on neural networks, but they require a comput…
Efficient Speech Quality Assessment using Self-supervised Framewise Embeddings
Karl El Hajal, Zihan Wu, Neil Scheidwasser-Clow +2
Automatic speech quality assessment is essential for audio researchers, developers, speech and language pathologists, and system quality engineers. The current state-of-the-art sys…
FastVC: Fast Voice Conversion with non-parallel data
Oriol Barbany Mayor, Milos Cernak
This paper introduces FastVC, an end-to-end model for fast Voice Conversion (VC). The proposed model can convert speech of arbitrary length from multiple source speakers to multipl…
Spiking neural networks trained with backpropagation for low power neuromorphic implementation of voice activity detection
Flavio Martinelli, Giorgia Dellaferrera, Pablo Mainar +1
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 requires fu…