A Review of Studies on Speech Generation and Recognition

Abstract

Voice recognition software is crucial to every
person's daily existence. It is a piece of
software that enables voice control of a user's
mobile device. Voice recognition software
breaks audio from such a speech into several
acoustic waveforms, analyses every sound
form, and afterwards resends each sound into
text using a different algorithm to find the
most accurate description in that language.
This essay will use examples from well-known
systems like Siri, Cortana, Google Assistant,
Alexa, and Bixby. In addition, this essay
analyses the relationship between speech
recognition and NLP (natural language
processing). Also, to get the greatest results,
our primary goal is to identify the speech
recognition method that is the most accurate
a comparative evaluation. Speech recognition
was not as successful at the time of its
conception or in its early stages as it is now, so
many researchers worked on this domain and
made it among the most exceptional aspects.
This document highlights a few of the
significant contributions or modifications
made by researchers to make automated
speech recognition (ASR) work as it does
presently. This paper discusses how voice
recognition, with the help of mobile personal
assistants, has changed the way the world is
now and how automatic speech recognition
technology works. In this work, we reviewed
brief voice recognition techniques, extracting
features methods, and speech recognition
kinds. This article additionally discusses
applications of voice recognition since its
beginnings. This study also demonstrates
speech recognition algorithms as well as
matching strategies such as whole word
match and sub-word match. A literary survey
depicts the history of inventions and
achievements in voice recognition. This paper
addresses the entire topic of speech
recognition