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@article{168948,
        author = {Lakshmi. S. Panicker and Rahul. C and R. Gopikakumari},
        title = {Development of an Advanced Mapped Real Transform for Enhanced Feature Extraction in Language Translation Application using Machine Learning},
        journal = {International Journal of Innovative Research in Technology},
        year = {2024},
        volume = {11},
        number = {6},
        pages = {77-87},
        issn = {2349-6002},
        url = {https://ijirt.org/article?manuscript=168948},
        abstract = {The majority of applications for signal processing involve changing signals from one domain to another. A common frequency domain representation is the discrete Fourier transform (DFT), which depicts the relative contribution of each frequency component in terms of complex sinusoids. The 2-D Mapped Real Transform (2-D MRT) is a very redundant and expansive transform that was proposed by changing 2-D DFT computations in terms of real additions by taking advantage of the periodicity and symmetry properties of the twiddle factor. Therefore, 2-D Unique MRT (2-D UMRT), which has the same size as the original signal, was proposed by detecting unique MRT coefficients. The phase components of a given frequency, however, are arranged in a scattered manner. The shortcomings of 2-D UMRT were addressed by the development of 2-D Sequency-based MRT (2-D SMRT). Still, only signals of size N with a power of 2 can be used with SMRT. MRT is extended for 1-D signals as well, while being developed initially for 2-D signals. The development of a new independent integer-to-integer transform, called 1-D GMRT, derived from 1-D MRT, is presented. It features the use of unique MRT coefficients that are ordered in terms of Greatest Common Divisor (GCD) values rather than sequency values for any N condition. The utilization of this transform in a speech translation application is also presented and in comparison, with traditional methods, the current system indicates an improvement of 10% in performance.},
        keywords = {DFT, GMRT, 1-D transform, Unique MRT, speech translation, language processing},
        month = {November},
        }