Speech coding is the process of compressing speech signals for transmission and storage
in communication systems. In recent years, speech coding has become increasingly …

We propose a subconvolutional U-net with a gated recurrent unit and an efficient channel
attention mechanism for real-time speech enhancement. The subconvolutional U-net (SCU …

Recent advancements in deep learning-based speech enhancement models have
extensively used attention mechanisms to achieve state-of-the-art methods by …

This paper proposes an innovative single-channel supervised speech enhancement (SE)
method based on UNET, a convolutional neural network (CNN) architecture that expands on …

Methods for extracting features from time series data using deep learning have been widely
studied, but they still suffer from problems of severe loss of feature information across …

Deep-learning models have used attention mechanisms to improve quality and intelligibility
of noisy speech, demonstrating the effectiveness of attention mechanisms. We rely on either …

Deep convolutional neural networks have achieved great success in the fields of medical
image segmentation and assisted diagnosis due to their excellent autonomous feature …

This dissertation explores mechanisms for understanding and improving speech processing.
First, I used EEG to investigate the acoustic and semantic processing of continuous …

E-commerce is becoming increasingly dependent on technologies such as consumer
sentiment research at an ever-increasing rate. Its purpose is to recognize and comprehend …