… Equally important is the development of the deep learning techniques in large vocabulary
continuous speech recognition (LVCSR) powered by big data and significantly increased …

… This work demonstrates the challenges faced by speech recognition systems developed to
automatically recognize children speech. For example, it has been shown that children below …

… speech recognition systems for various languages worldwide. Automatic speech recognition
has been viewed as successive transformations of acoustic micro structure of speech signal …

… statistical modeling of speech in the 1980s, automatic speech recognition systems today
find … automatic speech recognition technology to appropriately route and handle the calls [3]. …

… Hence, this section discusses the first speech recognition system followed by the … Most
of the speech recognition models are developed using a generic model. This generic …

… in the area of speech recognition still very active. A detailed study on automatic speech
recognition is carried out and presented in this paper that covers the architecture, speech …

… review of Automatic Speech Recognition. … Speech recognition System focuses on difficulties
with ASR, basic building blocks of speech processing, feature extraction, speech recognition …

ASR has already been researched and applied as a HCI for over thirty years [6]. Normally,
in order to apply speech recognition, an entire system needs to be developed from scratch. …

… The following content of this paper is organized as follows: In Section 2, we briefly reviewed
the history of automatic speech recognition, focus on introducing the basic ideas and …

The main task of automatic speech recognition (ASR) is to convert voice signals to text
transcriptions. It is one of the most important research fields in natural language processing (NLP)…