7 accepted papers
Efficiently deploying deep neural networks on low-resource edge devices is challenging due to their ever-increasing resource requirements. To address this issue, researchers have proposed multiplication-free neural networks, such as Power-of-Two quantization, or also known as Shift networks, which a…
Entity linking, bridging mentions in the contexts with their corresponding entities in the knowledge bases, has attracted wide attention due to many potential applications. Recently, plenty of multimodal entity linking approaches have been proposed to take full advantage of the visual information ra…
There is a growing body of work in recent years to develop pre-trained language models (PLMs) for the Arabic language. This work addresses two major problems in existing Arabic PLMs that limit the progress of the Arabic NLU and NLG fields. First, existing Arabic PLMs are not well-explored and their…
End-to-end spoken language understanding (SLU) recently attracted increasing interest. Compared to the conventional tandem-based approach that combines speech recognition and language understanding as separate modules, the new approach extracts users' intentions directly from the speech signals, res…
The transformer architecture has shown great capability in learning long-term dependency and works well in multiple domains. However, transformer has been less considered in audio-visual speech enhancement (AVSE) research, partly due to the convention that treats speech enhancement as a short-time s…
Most existing audio-visual speech enhancement (AVSE) methods work well in conditions with strong noise, however when applied to conditions with a medium SNR, serious performance degradations are often observed. These degradations can be partly attributed to the feature-fusion(early fusion etc.) arch…
Label Distribution Learning (LDL) is a general learning framework which includes both single label and multi-label learning as its special cases. One of the main assumptions made in traditional LDL algorithms is the derivation of the parametric model as the maximum entropy model. While it is a reaso…