Abstract
The emotional speech recognition method presented in this article was applied to recognize the emotions of students during online exams in distance learning due to COVID-19. The purpose of this method is to recognize emotions in spoken speech through the knowledge base of emotionally charged words, which are stored as a code book. The method analyzes human speech for the presence of emotions. To assess the quality of the method, an experiment was conducted for 420 audio recordings. The accuracy of the proposed method is 79.7% for the Kazakh language. The method can be used for different languages and consists of the following tasks: capturing a signal, detecting speech in it, recognizing speech words in a simplified transcription, determining word boundaries, comparing a simplified transcription with a code book, and constructing a hypothesis about the degree of speech emotionality. In case of the presence of emotions, there occurs complete recognition of words and definitions of emotions in speech. The advantage of this method is the possibility of its widespread use since it is not demanding on computational resources. The described method can be applied when there is a need to recognize positive and negative emotions in a crowd, in public transport, schools, universities, etc. The experiment carried out has shown the effectiveness of this method. The results obtained will make it possible in the future to develop devices that begin to record and recognize a speech signal, for example, in the case of detecting negative emotions in sounding speech and, if necessary, transmitting a message about potential threats or riots.
Highlights
Automatic recognition of human emotions is a new and interesting area of research.Achievements in the field of artificial intelligence are used in the development of affective computing and creation of emotional machines [1–3].Today, research is being carried out on recognizing facial emotions from videos [4–14], on determining emotions by voice rh2ythm from audio information [15–18], and by writing style from texts [19–21]
Work [27] proposes key technologies for recognition of speech emotions based on neural networks and recognition of facial emotions based on SVM, and in paper [28], they show a system of emotion recognition based on an artificial neural network (ANN) and its comparison with a system based on the scheme Hidden Markov Modeling (HMM)
The results of this work were from a method for recognizing emotional speech based on the emotion recognition model and the emotional vocabulary of emotionally charged words of the Kazakh language with generalized transcription, as well as from a code book
Summary
Automatic recognition of human emotions is a new and interesting area of research.Achievements in the field of artificial intelligence are used in the development of affective computing and creation of emotional machines [1–3].Today, research is being carried out on recognizing facial emotions from videos [4–14], on determining emotions by voice rh2ythm from audio information [15–18], and by writing style from texts [19–21]. Work [27] proposes key technologies for recognition of speech emotions based on neural networks and recognition of facial emotions based on SVM, and in paper [28], they show a system of emotion recognition based on an artificial neural network (ANN) and its comparison with a system based on the scheme Hidden Markov Modeling (HMM). Both systems were built on the basis of probabilistic pattern recognition and acoustic phonetic modeling approaches.
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