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Implementation of phonetic level speech recognition system for Punjabi language

机译:旁遮普语语音语音识别系统的实现

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This paper explains the implementation of the phonetic level speech recognition system for Punjabi language because it is a highly prosodic language. Here Hidden Markov Toolkit (HTK) is used. First step is data collection and nine hours data is collected in read speech mode. Second step is data preparation, in which hmmlist, grammar and dictionary files are created. Once the data is prepared, 75% and 25% of data is used for training and testing respectively. The experimental results show that the accuracy of the system increases from 49.95% to 59.38% as number of phonetic unit's increases from 30 to 34 and data increases from 3 hours to 6 hours respectively.
机译:本文解释了旁遮普语的语音级语音识别系统的实现,因为它是一种高度韵律的语言。这里使用隐马尔可夫工具包(HTK)。第一步是数据收集,然后以语音朗读模式收集9个小时的数据。第二步是数据准备,其中将创建hmmlist,语法和字典文件。一旦准备好数据,分别将75%和25%的数据用于培训和测试。实验结果表明,随着语音单元数量从30个增加到34个以及数据从3小时增加到6小时,该系统的准确性从49.95%增加到59.38%。

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