Advancements in structural health monitoring (SHM) techniques have spiked in the past few
decades due to the rapid evolution of novel sensing and data transfer technologies. This …

Deep learning based on neural networks has been widely used in image recognition,
speech recognition, natural language processing, automatic driving, and other fields and …

This article is a survey of deep learning methods for single and multiple sound source
localization, with a focus on sound source localization in indoor environments, where …

Automatic Speech Recognition (ASR), also known as Speech-To-Text (STT) or computer
speech recognition, has been an active field of research recently. This study aims to chart …

In various research domains, artificial intelligence (AI) has gained significant prominence,
leading to the development of numerous learning-based models in research laboratories …

Permutation ambiguity is a crucial issue for deep learning based talker-independent
speaker separation. Deep clustering and permutation invariant training (PIT) have been …

The binaural microphone, which refers to a pair of microphones with artificial human-shaped
ears, is widely used in hearing aids and spatial audio recording to improve sound quality. It …

Continuous speaker separation aims to separate overlap** speakers in real-world
environments like meetings, but it often falls short in isolating speech segments of a single …

Accurate diagnosis of the damage location of the frame structure is very important for the
overall damage assessment and subsequent maintenance of the frame structure. However …

Speaking of speech recognition within the English language, it is the process of recognizing
oral speech and transcribing it into writing using exclusive algorithms. For the perishable …