4 citations · 7 across the 7 of their papers we have counts for
7 papers
Deep low-latency joint speech transmission and enhancement over a gaussian channel
Mohammad Bokaei, Jesper Jensen, Simon Doclo +1
Ensuring intelligible speech communication for hearing assistive devices in low-latency scenarios presents significant challenges in terms of speech enhancement, coding and transmi…
How to train your ears: Auditory-model emulation for large-dynamic-range inputs and mild-to-severe hearing losses
Peter Leer, Jesper Jensen, Zheng-Hua Tan +2
Advanced auditory models are useful in designing signal-processing algorithms for hearing-loss compensation or speech enhancement. Such auditory models provide rich and detailed de…
Binaural Speech Enhancement Using Deep Complex Convolutional Transformer Networks
Vikas Tokala, Eric Grinstein, Mike Brookes +3
Studies have shown that in noisy acoustic environments, providing binaural signals to the user of an assistive listening device may improve speech intelligibility and spatial aware…
Self-supervised Pretraining for Robust Personalized Voice Activity Detection in Adverse Conditions
Holger Severin Bovbjerg, Jesper Jensen, Jan Østergaard +1
In this paper, we propose the use of self-supervised pretraining on a large unlabelled data set to improve the performance of a personalized voice activity detection (VAD) model in…
On Speech Pre-emphasis as a Simple and Inexpensive Method to Boost Speech Enhancement
Iván López-Espejo, Aditya Joglekar, Antonio M. Peinado +1
Pre-emphasis filtering, compensating for the natural energy decay of speech at higher frequencies, has been considered as a common pre-processing step in a number of speech process…
Speech inpainting: Context-based speech synthesis guided by video
Juan F. Montesinos, Daniel Michelsanti, Gloria Haro +2
Audio and visual modalities are inherently connected in speech signals: lip movements and facial expressions are correlated with speech sounds. This motivates studies that incorpor…