432 citations
- Centre National de la Recherche ScientifiqueFR5 papers
- Istanbul Technical UniversityTR5 papers
- University of WolverhamptonGB4 papers
- Helmholtz-Zentrum Berlin für Materialien und EnergieDE3 papers
- Observatoire de ParisFR3 papers
- Queen's University BelfastGB3 papers
- Shanghai Ocean UniversityCN3 papers
- University of GlasgowGB3 papers
- Chinese Academy of SciencesCN2 papers
- Fudan UniversityCN2 papers
- Janssen (France)FR2 papers
- Laboratoire Univers et ThéoriesFR2 papers
4 papers · 1 filter
Canonical Cortical Graph Neural Networks and its Application for Speech Enhancement in Audio-Visual Hearing Aids
Leandro A. Passos, João Paulo Papa, Amir Hussain +1
Despite the recent success of machine learning algorithms, most models face drawbacks when considering more complex tasks requiring interaction between different sources, such as m…
Multimodal Audio-Visual Information Fusion using Canonical-Correlated Graph Neural Network for Energy-Efficient Speech Enhancement
Leandro Aparecido Passos, João Paulo Papa, Javier Del Ser +2
This paper proposes a novel multimodal self-supervised architecture for energy-efficient audio-visual (AV) speech enhancement that integrates Graph Neural Networks with canonical c…
AV Speech Enhancement Challenge using a Real Noisy Corpus
Mandar Gogate, Ahsan Adeel, Kia Dashtipour +2
This paper presents, a first of its kind, audio-visual (AV) speech enhacement challenge in real-noisy settings. A detailed description of the AV challenge, a novel real noisy AV co…
CochleaNet: A Robust Language-independent Audio-Visual Model for Speech Enhancement
Mandar Gogate, Kia Dashtipour, Ahsan Adeel +1
Noisy situations cause huge problems for suffers of hearing loss as hearing aids often make the signal more audible but do not always restore the intelligibility. In noisy settings…