This study presents a valuable advance in reconstructing naturalistic speech from intracranial ECoG data using a dual-pathway model. The evidence supporting the claims of the authors is solid, ...

Abstract: This paper addresses the problem of recognising speech in the presence of a competing speech source. A novel two stage approach is described. A spectral representation is first divided into ...

Abstract: Deep-learning-based watermarking technique is being extensively studied. Most existing approaches adopt a similar encoder-driven scheme which we name END (Encoder-NoiseLayer-Decoder) ...

A major direction of Deep Learning in audio, especially generative models, is using features in frequency domain because directly model raw time signal is hard. But this require an extra process to ...

We propose an encoder-decoder for open-vocabulary semantic segmentation comprising a hierarchical encoder-based cost map generation and a gradual fusion decoder. We introduce a category early ...