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Hybrid HMM/ANN based isolated Hindi word recognition

机译:杂交嗯/神安基于孤立的印地语字识别

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Automatic speech recognition has become one of the most challenging task in the field of pattern recognition and natural language processing. In this paper, a hybrid model is proposed for isolated Hindi word recognition. This hybrid model involves the iterative training procedure. HMM is employed to induce the state transition probability distribution and ANN is employed as a classifier. HMM is designed by 4-state left to right model. In the proposed model ten Hindi words are used for the samples and five speakers for training and five distinct speakers for testing purpose and therefore the performance has achieved upto 89.8%.
机译:自动语音识别已成为模式识别和自然语言处理领域最具挑战性的任务之一。 本文提出了一种混合模型,用于隔离印地语字识别。 这种混合模型涉及迭代培训程序。 使用HMM诱导状态转换概率分布,并且ANN采用分类器。 HMM由4状态设计为左右模型。 在拟议的模型中,十个印地语单词用于样品和五位发言者,用于培训和五个不同的扬声器,用于测试目的,因此表现已达到89.8%。

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