Ensemble Feature Extraction Modules for Improved Hindi Speech Recognition System
نویسنده
چکیده
Speech is the most natural way of communication between human beings. The field of speech recognition generates intrigues of man – machine conversation and due to its versatile applications; automatic speech recognition systems have been designed. In this paper we are presenting a novel approach for Hindi speech recognition by ensemble feature extraction modules of ASR systems and their outputs have been combined using voting technique ROVER. Experimental results have been shown that proposed system will produce better result than traditional ASR systems.
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