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Kannada speech to text conversion using CMU Sphinx

This paper investigates the complex problem of speech to text conversion of Kannada Language. We propose a novel Kannada Automated Speech to Text conversion System (ASTC). We train and test the Speech Processing System using CMU Sphinx framework. CMU Sphinx is dynamic in nature with support for other languages along with English. We train the Acoustic model for Kannada speech with 1000 general spoken sentences and tested 150 sentences. We build our system utilizing features available in CMU Sphinx, thus showcasing the conceivable flexibility of this framework for Kannada voice to text conversion. In this paper, Kannada sentences with four to ten word length is researched. The speech conversion system permits ordinary people to speak to the computer in order to retrieve information in textual form. The number of alphabets in Kannada are 52. The system investigates extensibility of recognizing all letters and morphological variants of spoken Kannada words.