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Erschienen in:
2010 | OriginalPaper | Buchkapitel
Speaker Independent Urdu Speech Recognition Using HMM
verfasst von : Javed Ashraf, Naveed Iqbal, Naveed Sarfraz Khattak, Ather Mohsin Zaidi
Erschienen in: Natural Language Processing and Information Systems
Verlag: Springer Berlin Heidelberg
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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.