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Analysis on Regularity of Speech Energy based on Optimal Thresholding for Tamil Stuttering Dataset

机译:基于最优阈值的泰米尔口吃数据集语音能量规律性分析

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All over the world millions of people were affected by speech disorders in which one of the significant speech disorders is stuttering. Over the past two decade immense number of research is going on in the field of fluency disorder, and still it is necessary to enhance the analysis of stuttering disorder regional-wise. The speech signal tempo will vary with each individual where the specific fluctuation in the velocity of stutter speech is typical and it is due to the intervals in the speech rate which has a significant difference in normal stuttered speech. In this paper, Regularity of Speech Energy (RSE) was analyzed as normal, moderate and severe through Tamil speaking stuttered dataset. The analysis was done based on the energy threshold obtained during the irregular release of energy which is henceforth analyzed using optimal thresholding based on Particle Swam optimization (PSO) and Synergistic Fibroblast optimization (SFO) techniques. In order to evaluate the experimental analysis on RSE, statistical measures such as mean, standard deviation, Mean Square Error (MSE) and Root Mean Square Error (RMSE) were calculated. The experimental results of analysis on RSE have proved that stuttered speaker’s signal releases low energy when compared to the normal speaker where the optimal threshold energy enhances the detection of hidden speech energy.
机译:全世界有数百万人受到言语障碍的困扰,其中严重的言语障碍之一是口吃。在过去的二十年中,在流利性障碍领域进行了大量的研究,仍然有必要在区域范围内加强对口吃性障碍的分析。语音信号的速度会随每个人的变化而变化,其中典型的口吃语音速度波动是典型的,这是由于语音速率的间隔在正常的口吃语音中有显着差异。本文通过泰米尔语口吃数据集分析了语音能量的规律性(RSE),包括正常,中度和重度。分析是基于在能量不规则释放过程中获得的能量阈值进行的,此后使用基于粒子游动优化(PSO)和协同成纤维细胞优化(SFO)技术的最佳阈值进行分析。为了评估RSE的实验分析,计算了诸如均值,标准差,均方误差(MSE)和均方根误差(RMSE)等统计量。对RSE进行分析的实验结果证明,与普通扬声器相比,口吃的扬声器信号释放的能量较低,而普通扬声器的最佳阈值能量可增强对隐藏语音能量的检测。

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