Implementation of Adaptive Neural Fuzzy Inference Systems (Anfis) For Speech Recognition Applications In Smart Home Control

Authors

  • Roni Permana Department of Primary Teacher Education, Faculty of Teacher Training and Education, Universitas Mandiri, Subang 41211, Indonesia
  • Mada Sanjaya WS Department of Physics, Faculty of Science and Technology, UIN Sunan Gunung Djati, Bandung, Indonesia
  • Hasniah Aliah Department of Physics, Faculty of Science and Technology, UIN Sunan Gunung Djati, Bandung, Indonesia

Keywords:

MFCC, ANFIS, Signal Processing Digital, Signal Processing, Control Systems

Abstract

Signal Processing is signal processing that is related to the presentation, transformation, and manipulation of signal content and information. Digital Signal Processing is signal processing that is related to the presentation, transformation, and manipulation of signal content and information in digital form. The speech control system is very efficient. Speech signals are signals that change over time at a relatively slow speed. If observed at short intervals (between 5 and 100 miles per second), the practical characteristics are constant, but if observed at longer intervals, the characteristics appear to change according to the sentences spoken. This study uses the signal pattern recognition method with the MFCC and ANFIS methods as learning. The performance results of the entire system obtained an accuracy value with 6 feature extractions in 2 respondents, namely 65% ​​-72.5% and the smarthome control system worked well.

References

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Published

2024-12-06

How to Cite

Roni Permana, Mada Sanjaya WS, & Hasniah Aliah. (2024). Implementation of Adaptive Neural Fuzzy Inference Systems (Anfis) For Speech Recognition Applications In Smart Home Control. TIME in Physics, 2(2), 77–84. Retrieved from http://ejournal.universitasmandiri.ac.id/index.php/timeinphys/article/view/143

Issue

Vol. 2 No. 2 (2024): September

Section

Articles

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Copyright (c) 2024 Roni Permana, Mada Sanjaya WS, Hasniah Aliah

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This work is licensed under a Creative Commons Attribution 4.0 International License.