Language and Text Independent Speaker Recognition System using Artificial Neural Networks and Fuzzy Logic
J Sirisha Devi
J Sirisha Devi, Department of Computer Science and Engineering Institute of Aeronautical Engineering, JNTU. Hyderabad, (Telangana), India.
Manuscript received on 24 March 2019 | Revised Manuscript received on 30 March 2019 | Manuscript published on 30 March 2019 | PP: 327-330 | Volume-7 Issue-6, March 2019 | Retrieval Number: F2115037619/19©BEIESP
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© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC-BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)
Abstract: In this era of technological advancement, the new techniques are evolving for better man-machine interaction. Initially, this urge of interacting with machines was the main reason behind invention of input-output devices like keyboard, mouse, monitor, printer, joystick, scanner, touch-screens, and trackball etc. However, none of these above said inventions are able to provide verbal interaction of human and machines, which is the natural means of communication for many centuries. This lack of communication with machines using speech leads the researchers towards inventing the speech processing systems for better human machine interaction using speech signals. In the present paper, the performance of an algorithm for language and text independent speaker recognition systems based on fuzzy logic and ANNs is evaluated. The efficiency of speaker recognition system with noisy speech samples of user defined database is higher than that of TIMIT database.
Keywords: Speaker Recognition, Artificial Neural Networks, Fuzzy Logic.
Scope of the Article: Natural Language Processing