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A Comprehensive View of Automatic Speech Recognition System - A Systematic Literature Review

机译:语音自动识别系统的全面介绍-系统文献综述

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Humans have always attempted to correspond with objects in a natural language. Communications have been the essential feature of human life, a powerful tool for sharing and building the information that is passed from generation to generation. Among speech processing problems, automatic speech recognition mechanisms of converting the recorded speech signals into the text are one of the most challenging tasks. The signals are typically processed in a digital representation, so speech processing can be observed as a particular case of digital signal processing. The overall performance of an automatic speech recognition system greatly depends upon the acoustic modeling. Hence, building a precise and robust acoustic model holds the key to a suitable recognition performance. People have used different methods for automated speech recognition system. For recognizing the speech people always choose the English language in the majority of the research and implementation but very less work is done in other languages. Our analysis presents the study of the different speech recognition systems present in Indian and foreign languages in the systematic review of speech recognition paper. This paper gives the review of different aspects related to Automatic Speech recognition. We have elaborated the recent advancement in the speech recognition system, robust method for the development of an automatic speech recognition system and application of automatic speech recognition system in different fields.
机译:人类一直试图与自然语言中的物体相对应。通讯已成为人类生活的基本特征,它是共享和构建代代相传信息的强大工具。在语音处理问题中,将记录的语音信号转换为文本的自动语音识别机制是最具挑战性的任务之一。信号通常以数字表示形式进行处理,因此可以将语音处理视为数字信号处理的特殊情况。自动语音识别系统的整体性能在很大程度上取决于声学模型。因此,建立精确而强大的声学模型是获得适当识别性能的关键。人们已经使用了不同的方法来实现自动语音识别系统。为了识别语音,人们在大多数研究和实现中总是选择英语,但是很少有其他语言的工作。我们的分析在对语音识别文件的系统回顾中介绍了对印度和外语中存在的不同语音识别系统的研究。本文概述了与自动语音识别相关的各个方面。我们详细介绍了语音识别系统的最新进展,开发自动语音识别系统的可靠方法以及自动语音识别系统在不同领域的应用。

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