Over the past decades, a tremendous amount of research has been done on the use of
machine learning for speech processing applications, especially speech recognition …

Convolutional neural networks (CNNs) have been applied to visual tasks since the late
1980s. However, despite a few scattered applications, they were dormant until the mid …

In deep learning, different kinds of deep networks typically need different optimizers, which
have to be chosen after multiple trials, making the training process inefficient. To relieve this …

Conformer has proven to be effective in many speech processing tasks. It combines the
benefits of extracting local dependencies using convolutions and global dependencies …

Given the recent surge in developments of deep learning, this paper provides a review of the
state-of-the-art deep learning techniques for audio signal processing. Speech, music, and …

Deep learning has become an area of interest to the researchers in the past few years.
Convolutional Neural Network (CNN) is a deep learning approach that is widely used for …

Feature extraction plays a vital role in intelligent fault diagnosis of mechanical system.
Nevertheless, traditional feature extraction methods suffer from three problems, which are …

These days, many recommender systems (RS) are utilized for solving information overload
problem in areas such as e-commerce, entertainment, and social media. Although classical …

In the last few years, deep learning has led to very good performance on a variety of
problems, such as visual recognition, speech recognition and natural language processing …

Traditional artificial methods and intelligence-based methods of classifying and diagnosing
various mechanical faults with high accuracy by extracting effective features from vibration …