Automatic Speech Recognition (ASR), which is aimed to enable natural human–machine
interaction, has been an intensive research area for decades. Many core technologies, such …

Recently great strides have been made in the field of automatic speech recognition (ASR) by
using various deep learning techniques. In this study, we present a thorough comparison …

Over the past few decades, there has been tremendous development in machine learning
paradigms used in automatic speech recognition (ASR) for home automation to space …

Automatic Speech Recognition (ASR) has historically been a driving force behind many
machine learning (ML) techniques, including the ubiquitously used hidden Markov model …

In spite of the advances accomplished throughout the last decades, automatic speech
recognition (ASR) is still a challenging and difficult task. In particular, recognition systems …

Recent advancements in deep learning (DL) have posed a significant challenge for
automatic speech recognition (ASR). ASR relies on extensive training datasets, including …

A huge amount of research has been done in the field of speech signal processing in recent
years. In particular, there has been increasing interest in the automatic speech recognition …

In recent years there has been a significant body of work, both theoretical and experimental,
that has established the viability of Artit~ cial Neural Networks (ANNs) as a useful …

Automatic speech recognition (ASR) has recently become an important challenge when
using deep learning (DL). It requires large-scale training datasets and high computational …

We present a state-of-the-art speech recognition system developed using end-to-end deep
learning. Our architecture is significantly simpler than traditional speech systems, which rely …