592 citations · 4.5k across the 68 of their papers we have counts for
10 papers · 1 filter
Narrow-band Deep Filtering for Multichannel Speech Enhancement
Xiaofei LI, Radu Horaud
In this paper, we address the problem of multichannel speech enhancement in the short-time Fourier transform (STFT) domain. A long short-time memory (LSTM) network takes as input a…
A Recurrent Variational Autoencoder for Speech Enhancement
Simon Leglaive, Xavier Alameda-Pineda, Laurent Girin +1
This paper presents a generative approach to speech enhancement based on a recurrent variational autoencoder (RVAE). The deep generative speech model is trained using clean speech…
Audio-visual Speech Enhancement Using Conditional Variational Auto-Encoders
Mostafa Sadeghi, Simon Leglaive, Xavier Alameda-PIneda +2
Variational auto-encoders (VAEs) are deep generative latent variable models that can be used for learning the distribution of complex data. VAEs have been successfully used to lear…
How To Train Your Deep Multi-Object Tracker
Yihong Xu, Aljosa Osep, Yutong Ban +3
The recent trend in vision-based multi-object tracking (MOT) is heading towards leveraging the representational power of deep learning to jointly learn to detect and track objects.…
Expectation-Maximization for Speech Source Separation Using Convolutive Transfer Function
Xiaofei Li, Laurent Girin, Radu Horaud
This paper addresses the problem of under-determinded speech source separation from multichannel microphone singals, i.e. the convolutive mixtures of multiple sources. The time-dom…
Audio-noise Power Spectral Density Estimation Using Long Short-term Memory
Xiaofei Li, Simon Leglaive, Laurent Girin +1
We propose a method using a long short-term memory (LSTM) network to estimate the noise power spectral density (PSD) of single-channel audio signals represented in the short time F…