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An Extensive Review of Feature Extraction Techniques, Challenges and Trends in Automatic Speech Recognition

机译:语音自动识别中特征提取技术,挑战和趋势的广泛综述

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Speech is the natural mode of communication between humans. Human-to-machine interaction is gaining importance in the past few decades which demands the machine to be able to analyze, respond and perform tasks at the same speed as performed by human. This task is achieved by Automatic Speech Recognition (ASR) system which is typically a speech-to-text converter. In order to recognize the areas of further research in ASR, one must be aware of the current approaches, challenges faced by each and issues that needs to be addressed. Therefore, in this paper human speech production mechanism is discussed. The various speech recognition techniques and models are addressed in detail. The performance parameters that measure the accuracy of the system in recognizing the speech signal are described.
机译:语音是人与人之间交流的自然方式。在过去的几十年中,人机交互越来越重要,这要求机器能够以与人类相同的速度分析,响应和执行任务。该任务通过自动语音识别(ASR)系统完成,该系统通常是语音到文本转换器。为了认识到ASR的进一步研究领域,必须认识到当前的方法,每种方法面临的挑战以及需要解决的问题。因此,本文讨论了人的语音产生机制。详细介绍了各种语音识别技术和模型。描述了测量系统识别语音信号准确性的性能参数。

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