Open AccessThe New Technique Enhancing of Automatic Speech Recognition System for ODIA Language using HTK Based On Hidden Markov Model (HMM)
Author(s) -
Prasanna Kumar Sahu,
Santisudha Panigrahi,
Umakant Bhaskar Gohatre
Publication year - 2020
Publication title -
international journal of recent technology and engineering
Language(s) - English
Resource type - Journals
ISSN - 2277-3878
DOI - 10.35940/ijrte.a2817.059120
Subject(s) - hidden markov model , computer science , java , speech recognition , interactivity , software , artificial intelligence , natural language processing , programming language , operating system
The purpose of this paper is to address the application to an Indian Regional Language, ODIA of a single word Automatically Speech Recognition System (ASRS). The toolkit is based on Hidden Markov Model (HMM). The details was obtained from 8 ODIA Language speakers. The program is then qualified for 205 different terms in ODIA. Samples from six separate speakers have again been obtained. This is then evaluated in real time. A GUI has been created to enhance the system's interactivity. We used and introduced the test framework for development of the GUI JAVA application. A comprehensive model of an ASR framework was developed to explain each HTK resource using HTK library modules and software. The findings of the experiment indicate that the overall machine efficiency is 93.45%.