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首页> 外文期刊>Oriental journal of computer science and technology >Phoneme Segmentation of Tamil Speech Signals Using Spectral Transition Measure
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Phoneme Segmentation of Tamil Speech Signals Using Spectral Transition Measure

机译:泰米尔语语音信号的音素分割使用频谱过渡测量

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Process of identifying the end points of the acoustic units of the speech signal is called speech segmentation. Speech recognition systems can be designed using sub-word unit like phoneme. A Phoneme is the smallest unit of the language. It is context dependent and tedious to find the boundary. Automated phoneme segmentation is carried in researches using Short term Energy, Convex hull, Formant, Spectral Transition Measure(STM), Group Delay Functions, Bayesian Information Criterion, etc. In this research work, STM is used to find the phoneme boundary of Tamil speech utterances. Tamil spoken word dataset was prepared with 30 words uttered by 4 native speakers with a high quality microphone. The performance of the segmentation is analysed and results are presented.
机译:识别语音信号的声学单元的端点的过程称为语音分段。可以使用子音单元(如音素)来设计语音识别系统。音素是该语言的最小单位。查找边界是上下文相关且繁琐的。使用短期能量,凸包,共振峰,光谱转变量度(STM),群时延函数,贝叶斯信息准则等进行自动音素分割的研究。在这项研究工作中,STM用于查找泰米尔语语音的音素边界。话语。泰米尔语的语音数据集由30位来自4位母语为母语的人说出的高质量语音麦克风准备而成。分析了分割的性能并给出了结果。

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