Speech Recognition: A Concise Significance

Speech Recognition and communication between humans and computers have made tremendous progress over the last three decades. Speech recognition technologies allow the machine to respond correctly to a human voice. Nowadays a lot of Automatic Speech Recognition Systems are developed which are more resistant to environmental, speaker, and language variability. The voice-based application provides valuable and useful services to the user. Deep learning is an emerging area, in the last few years research has focused on using it for speech-related different applications. Feature extraction, speech classifiers, speech representation, speech database, and performance are some important issues that should be considered while designing a speech recognition system. The challenges that exist in ASR, as well as the different methods developed by various researchers, have been described in sequence. This paper explores the significant advances in speech communication research over the years, also helps to identify a different tool along with its merits and demerits. The primary aim of the article is to conduct a comparison between various speech recognition methods. This paper shed light on the trends in speech recognition system and also bring focus to new research topics