Speech Emotion Recognition Using Fuzzy Logic Classifier

Over the last two decades, emotions, speech recognition and signal processing have been one of the most significant issues in the adoption of techniques to detect them. Each method has advantages and disadvantages. This paper tries to suggest fuzzy speech emotion recognition based on the classification of speech's signals in order to better recognition along with a higher speed. In this system, the use of fuzzy logic system with 5 layers, which is the combination of neural progressive network and algorithm optimization of firefly, first, speech samples have been given to input of fuzzy orbit and then, signals will be investigated and primary classified in a fuzzy framework. In this model, a pattern of signals will be created for each class of signals, which results in reduction of signal data dimension as well as easier speech recognition. The obtained experimental results show that our proposed method (categorized by firefly), improves recognition of utterances.