Speech to Text Processing for Interactive Agent of Virtual Tour Navigation

Dian Ahkam Sani, Muchammad Saifulloh

Abstract


The development of science and technology is one way to replace the method of human interaction with computers, one of which is to provide voice input. Conversion of sound into text form with the Backpropagation method can be understood and realized through feature extraction, including the use of Linear Predictive Coding (LPC). Linear Predictive Coding is one way to represent the signal in obtaining the features of each sound pattern. In brief, the way this speech recognition system worked was by inputting human voice through a microphone (analog signal) which then sampled with a sampling speed of 8000 Hz so that it became a digital signal with the assistance of sound card on the computer. The digital signal from the sample then entered the initial process using LPC, so that several LPC coefficients were obtained. The LPC outputs were then trained using the Backpropagation learning method. The results of the learning were classified with a word and stored in a database afterwards. The results of the test were in the form of an introduction program that able display the voice plots. the results of speech recognition with voice recognition percentage of respondents in the database iss 80% of the 100 data in the test in Real Time


Keywords


Sound; Linear Predictive Coding (LPC); Backpropagation

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DOI: http://dx.doi.org/10.25139/ijair.v1i1.2030

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Copyright (c) 2019 Dian Ahkam Sani, Muchammad Saifulloh

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International Journal of Artificial Intelligence & Robotics (IJAIR)
ISSN 2686-6269 (Online)
Published By Universitas Dr. Soetomo
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Inform is licensed under a Creative Commons Attribution-ShareAlike 4.0 International License.