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Malayalam Isolated Digit Recognition using HMM and PLP cepstral coefficient

机译:使用HMM和PLP倒谱系数的马拉雅拉姆语隔离数字识别

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Development of Malayalam speech recognition system is in its infancy stage; although many works have been done in other Indian languages. In this paper we present the first work on speaker independent Malayalam isolated speech recognizer based on PLP (Perceptual Linear Predictive) Cepstral Coefficient and Hidden Markov Model (HMM). The performance of the developed system has been evaluated with different number of states of HMM (Hidden Markov Model). The system is trained with 21 male and female speakers in the age group ranging from 19 to 41 years. The system obtained an accuracy of 99.5% with the unseen data
机译:马拉雅拉姆语语音识别系统的开发尚处于起步阶段;尽管已经用其他印度语言完成了许多工作。在本文中,我们介绍了基于PLP(感知线性预测)倒谱系数和隐马尔可夫模型(HMM)的独立于说话者的马拉雅拉姆语隔离语音识别器的第一项工作。已用不同数量的HMM状态(隐马尔可夫模型)评估了开发系统的性能。该系统接受了21位年龄在19至41岁之间的男性和女性演讲者的培训。该系统使用未知数据获得了99.5%的精度

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