The emerging field of artificial intelligence of things (AIoT, AI+ IoT) is driven by the
widespread use of intelligent infrastructures and the impressive success of deep learning …

Self-supervised learning (SSL) achieves great success in speech recognition, while limited
exploration has been attempted for other speech processing tasks. As speech signal …

This paper describes a dataset and protocols for evaluating continuous speech separation
algorithms. Most prior speech separation studies use pre-segmented audio signals, which …

This study proposes a complex spectral map** approach for single-and multi-channel
speech enhancement, where deep neural networks (DNNs) are used to predict the real and …

Continuous speech separation was recently proposed to deal with the overlapped speech in
natural conversations. While it was shown to significantly improve the speech recognition …

As the most widely-used spatial filtering approach for multi-channel speech separation,
beamforming extracts the target speech signal arriving from a specific direction. An …

Multi-speaker speech recognition of unsegmented recordings has diverse applications such
as meeting transcription and automatic subtitle generation. With technical advances in …

This study tightly integrates complementary spectral and spatial features for deep learning
based multi-channel speaker separation in reverberant environments. The key idea is to …