A speech recognition system for Urdu language

Azam Beg, S. K. Hasnain

    Research output: Chapter in Book/Report/Conference proceedingConference contribution

    2 Citations (Scopus)


    This paper investigates use of a machine learnt model for recognition of individually words spoken in Urdu language. Speech samples from many different speakers were utilized for modeling. Original time-domain samples are normalized and pre-processed by applying discrete Fourier transformation for speech feature extraction. In frequency domain, high degree of correlation was found for the same words spoken by different speakers. This helped produce models with high recognition accuracy. Details of model realization in MATLAB are included in this paper. Current work is being extended using linear predictive coding for efficient hardware implementation.

    Original languageEnglish
    Title of host publicationWireless Networks, Information Processing and Systems - International Multi Topic Conference, IMTIC 2008, Revised Selected Papers
    PublisherSpringer Verlag
    Number of pages9
    ISBN (Print)3540898522, 9783540898528
    Publication statusPublished - 2008

    Publication series

    NameCommunications in Computer and Information Science
    Volume20 CCIS
    ISSN (Print)1865-0929


    • Urdu speech processing
    • data pre-processing
    • feature extraction
    • machine learning
    • modeling
    • speaker independent system

    ASJC Scopus subject areas

    • General Computer Science
    • General Mathematics


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