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Speaker Independent Urdu Speech Recognition Using HMM

机译:使用HMM的扬声器独立的URDU语音识别

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摘要

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)的高级字段之一。最近过去在英语,欧洲和东亚语言中见证了ASR的宝贵研究活动。但遗憾的是,南亚语言一般和“乌尔都语”特别受到严重的关注。在本文中,我们提出了一种为乌尔都语语言开发ASR系统的方法。该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:隐藏的Markov模型)来开发ASR系统。我们向小型大小词汇提供了一名扬声器独立的ASR系统,即50次孤立的大多数口语乌尔德语言,并提出了这项研究工作将形成开发中型和大型词汇乌尔都语语音识别系统的基础。

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