An intelligent voice recognition system based on fuzzy logic and the bag-of-words technique

Abstract

This paper describes a method for recognizing voice command based on a fuzzy logic system capable of perceiving fuzzy commands, i.e. commands containing fuzzy terms, for example, ‘close’, ‘closer’, ‘close to’, ‘closer than’, ‘further’ and ‘very far’. The developed approach has the ability to be trained for a specific user. The developed fuzzy logic system is used to recognize linguistically inaccurate commands in order to increase the expressiveness of the language for control of a moving robot.

A Framework for Smart Home System with Voice Control Using NLP Methods

“…The new home automation system applies a Google voice recognition service and a microcontroller to execute certain voice commands. Stefanenko et al [30] described a method for voice commands recognition based on fuzzy logic. The developed fuzzy system has been employed to execute linguistically inaccurate commands.…”

“…Voice user interface can be implemented only by integration of methods covering all aspects of natural language processing (voice data entry, tokenisation, lemmatisation, tagging, semantic analysis); 2. Intent detection methods can be categorised into three main groups:  Methods using statistical features (hidden Markov model, dynamic time warping, naive Bayes, AdaBoost, support vector machines, logistic regression) [28];  Neural networks (convolutional neural networks, recurrent neural networks) and deep learning (LSTM), distance-based (Term Frequency-Inverse Document Frequency-TF-IDF) methods or combination of several deep learning methods [25,26];  Other intelligent methods for semantic recognition of voice commands (fuzzy logic [30], semantic patterns). 3.…”