DocumentCode :
515396
Title :
Speaker Independent Urdu speech recognition using HMM
Author :
Ashraf, Javed ; Iqbal, Naveed ; Khattak, Naveed Sarfraz ; Zaidi, Ather Mohsin
Author_Institution :
Coll. of Signals, Nat. Univ. of Sci. & Technol. (NUST), Rawalpindi, Pakistan
fYear :
2010
fDate :
28-30 March 2010
Firstpage :
1
Lastpage :
5
Abstract :
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 (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.
Keywords :
hidden Markov models; natural language processing; speech recognition; ASR system; East Asian languages; English languages; European languages; HMM; South Asian Languages; Sphinx4; automatic speech recognition; hidden Markov model; natural language processing; speaker independent Urdu speech recognition; statistical based approach; Automatic speech recognition; Educational institutions; Hidden Markov models; Mathematical model; Natural language processing; Natural languages; Signal processing; Speech recognition; Strontium; Vocabulary; CMU Sphinx4; Hidden Markov Model; Speech Recognition; Urdu language;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Informatics and Systems (INFOS), 2010 The 7th International Conference on
Conference_Location :
Cairo
Print_ISBN :
978-1-4244-5828-8
Type :
conf
Filename :
5461790
Link To Document :
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