Open AccessTelugu Speech Recognition on TRI-SPECTRAL and DNN Techniques
Author(s) -
C. Kumar,
Archek Praveen Kumar,
Bhawna Priya,
Affrose,
A. Haseena
Publication year - 2019
Publication title -
international journal of recent technology and engineering
Language(s) - English
Resource type - Journals
ISSN - 2277-3878
DOI - 10.35940/ijrte.d5255.118419
Subject(s) - telugu , computer science , speech recognition , interfacing , focus (optics) , feature (linguistics) , software , feature extraction , artificial intelligence , pattern recognition (psychology) , natural language processing , computer hardware , linguistics , philosophy , physics , optics , programming language
his Research focus on the recognition of speech signals for Telugu language. The data of Telugu language considered is in isolated format. 10 isolated words are considered which are frequently spoken and recognized. Advanced technique named Tri spectral technique and DNN is used for this recognition. Tri spectral is a feature extraction technique. DNN is a feature classification technique. This research can be used in many interfacing systems which helps the humans to interact with the hardware or software systems easily. Design of ASR (“Automatic Speech Recognition System”) deals with many parameters which should finally conclude with promising recognition results. This techniques used in this research has given a better result with the accuracy of approximately 96.27%.