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Speaker Independent Urdu Speech Recognition Using HMM

机译:使用HMM的独立于说话人的乌尔都语语音识别

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Automatic Speech Recognition (ASR) is one of the advanced fields of Natural Language Processing (NLP). Recent past has witnessed valuable research activities in ASR in English, European and East Asian languages. But unfortunately South Asian Languages in general and "Urdu" in particular have received very less attention. In this paper we present an approach to develop an ASR system for Urdu language. The proposed system is based on an open source speech recognition framework called Sphinx4 which uses statistical based approach (HMM: Hidden Markov Model) for developing ASR system. We present a Speaker Independent ASR system for small sized vocabulary, i.e. fifty two isolated most spoken Urdu words and suggest that this research work will form the basis to develop medium and large size vocabulary Urdu speech recognition system.
机译:自动语音识别(ASR)是自然语言处理(NLP)的高级领域之一。最近,目睹了用英语,欧洲和东亚语言进行的ASR有价值的研究活动。但是不幸的是,总体上南亚语言,尤其是“乌尔都语”很少受到关注。在本文中,我们提出了一种开发针对乌尔都语语言的ASR系统的方法。提出的系统基于名为Sphinx4的开源语音识别框架,该框架使用基于统计的方法(HMM:隐马尔可夫模型)来开发ASR系统。我们提出了一种针对小词汇量的独立于说话人的ASR系统,即52个孤立的乌尔都语最孤立的单词,并建议这项研究工作将成为开发中型和大尺寸词汇Urdu语音识别系统的基础。

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