自动语音识别:综合调查

Amarildo Rista, A. Kadriu
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引用次数: 3

摘要

语音识别是自然语言处理(NLP)的一个跨学科子领域,它促进了机器对口语的识别和翻译。语音识别在数字化转型中发挥着重要作用。它被广泛应用于教育、工业和医疗保健等不同领域,最近还被用于许多物联网和机器学习应用。语音识别过程是计算机科学中最困难的过程之一。尽管在这一领域进行了大量的研究,但尚未找到一种最佳的语音识别方法。这是因为自然语言有许多特征,每种语言都有其特殊的亮点。本研究的目的是通过对现有工作的系统文献综述,提供对语音识别领域内各种技术的全面理解。我们将介绍最重要和相关的技术,可能为未来的研究提供一些方向。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Automatic Speech Recognition: A Comprehensive Survey
Abstract Speech recognition is an interdisciplinary subfield of natural language processing (NLP) that facilitates the recognition and translation of spoken language into text by machine. Speech recognition plays an important role in digital transformation. It is widely used in different areas such as education, industry, and healthcare and has recently been used in many Internet of Things and Machine Learning applications. The process of speech recognition is one of the most difficult processes in computer science. Despite numerous searches in this domain, an optimal method for speech recognition has not yet been found. This is due to the fact that there are many attributes that characterize natural languages and every language has its particular highlights. The aim of this research is to provide a comprehensive understanding of the various techniques within the domain of Speech Recognition through a systematic literature review of the existing work. We will introduce the most significant and relevant techniques that may provide some directions in the future research.
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