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Techniques and applications of emotion recognition in speech

Sergej Lugović · Ivan Đunđer · Marko Horvat

67 citations0/0 files storedInternational Convention on Information and Communication Technology, Electronics and Microelectronics

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Emotion and Mood Recognition Speech Recognition and Synthesis Sentiment Analysis and Opinion Mining

Abstract

Affective computing opens a new area of research in computer science with the aim to improve the way how humans and machines interact. Recognition of human emotions by machines is becoming a significant focus in recent research in different disciplines related to information sciences and Human-Computer Interaction (HCI). In particular, emotion recognition in human speech is important, as it is the primary communication tool of humans. This paper gives a brief overview of the current state of the research in this area with the aim to underline different techniques that are being used for detecting emotional states in vocal expressions. Furthermore, approaches for extracting speech features from speech datasets and machine learning methods with special emphasis on classifiers are analysed. In addition to the mentioned techniques, this paper also gives an outline of the areas where emotion recognition could be utilised such as healthcare, psychology, cognitive sciences and marketing.

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References

1997Affective Computing 2005A database of German emotional speech 2003Speech emotion recognition using hidden Markov models 1950The Human Use of Human Beings 2011Recognising realistic emotions and affect in speech: State of the art and lessons learnt from the first challenge 1995Passion and reason: making sense of our emotions 1994Passion and Reason 2011Emotion recognition using a hierarchical binary decision tree approach

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2022A Review of AI Cloud and Edge Sensors, Methods, and Applications for the Recognition of Emotional, Affective and Physiological States 2018Cubic SVM Classifier Based Feature Extraction and Emotion Detection from Speech Signals 2022RobinNet: A Multimodal Speech Emotion Recognition System With Speaker Recognition for Social Interactions 2021Context-Aware Emotion Recognition Based on Visual Relationship Detection 2023Speech emotion recognition system using gender dependent convolution neural network 2019

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