病理语音的实验语音识别

Hadji Salah
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引用次数: 0

摘要

语音识别已经成为不少研究课题的主题,因为它是动态,高效和互动的适当手段,人类交流同时使用说话者之间的发音和听力这两种现象,其搜索的应用是巨大的,例如可以引用:听写,Windows软件中的语音合成,智能手机级别的谷歌搜索引擎的语音识别...... ..等。其所有应用程序依赖于实现它们的使用条件,要做和克服缺陷的谜题需要确保正确地描述语音信号的提取最相关的人物,如:基频(音高英文),音色、音调,提取他们的许多技术是可行的,最常用的声如:MFCC, PLP, LPC,拉斯塔和其他形式的组合(杂交)即:PLP RASTA, MFCC PLP等。它们被用于数据传输、说话人识别甚至语音合成。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Experimental Speech Recognition From Pathological Voices
Speech recognition has been the subject of quite a few research subjects as it is the adequate means for dynamic, efficient and interaction Human communication simultaneously using the two phenomena of phonation and hearing between speakers, the applications of its searches are enormous for example one can quote: the dictation, the speech synthesis within the Windows software, the speech recognition of the Google search engine at the Smartphone level …… ..etc. all its applications depend on the conditions of use in which they are implemented, to be done and to overcome the puzzles of imperfection it is necessary to be sure to properly characterize the speech signal by extracting the most relevant characters such as: the fundamental frequency (pitch in English), timbre, tonality, to extract them many techniques are possible, the most used of which are acoustic such as: MFCC, PLP, LPC, RASTA and other in the form of combination (hybridization) namely: PLP RASTA, MFCC PLP etc. They are used in data transmission, speaker recognition and even in speech synthesis.
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