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@article{144715,
        author = {Nitesh Patel and Aparna P. Laturkar},
        title = {OPTIMIZED APPROACH OF VOICE RECOGNISATION },
        journal = {International Journal of Innovative Research in Technology},
        year = {},
        volume = {4},
        number = {2},
        pages = {273-280},
        issn = {2349-6002},
        url = {https://ijirt.org/article?manuscript=144715},
        abstract = {Speech is one of the most important manners of communication for humans, to exchange feelings and information. Speech is the most efficient way to train a machine or communicate with a machine. Detection systems lies on hidden Markov models are successful under exacting situation, but do undergo from main restrictions that limit applicability of ASR technology in real-world environments. However, over the last few years, several attempts have been undergone to evaluate the HMM deficiencies. Artificial Neural Networks (ANN) and more specifically Multi-Layer Perception’s (MLP) appeared to be a promising alternative in this respect to replace or help HMM in the classification mode. Algorithms are applied to reduce the noise interference and silence suppression. The signal free from above interference is then processed to extract the features. MFCC is used as a feature extraction technique.},
        keywords = {Hidden Markov models(HMM), Artificial Neural Networks (ANN), Multi-Layer Perception’s (MLP)},
        month = {},
        }