Emotion Recognition: A Pattern Analysis Approach by Amit Konar

By Amit Konar

  • Offers either foundations and advances on emotion reputation in one volume
  • Provides an intensive and insightful creation to the topic through the use of computational instruments of various domains
  • Inspires younger researchers to arrange themselves for his or her personal research
  • Demonstrates course of destiny learn via new applied sciences, corresponding to Microsoft Kinect, EEG structures etc.

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Additional info for Emotion Recognition: A Pattern Analysis Approach

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They chose 27 subjects and recorded their videos of facial and bodily responses while watching 20 emotional videos. Features used for their experiment include distance metrics of the eye, eyebrow, and mouth as facial features, audio and vocal expressions, eye FEATURE REDUCTION TECHNIQUES 15 gaze, pupil size, electrocardiograph (ECG), galvanic skin response (GSR), respiration amplitude, and skin temperature as physiological features. The main contribution of this research lies in the development of a large database of recorded modalities with high qualitative synchronization between them making it valuable to the ongoing development and benchmarking of emotion-related algorithms.

2 Voice Features Voice features used for emotion recognition include prosodic and spectral features. Prosodic features are derived from pitch, intensity, and first formant frequency profiles as well as voice quality measures. Spectral features include Mel-frequency cepstral coefficients (MFCC), linear prediction cepstral coefficients (LPC), log frequency power coefficients (LFPC), perceptual linear prediction (PLP) coefficients. We now briefly provide an overview of the voice features below. 1.

Of Materials Science and Engineering, University of Ioannina, Ioannina,and Dept. of Economics, University of Ioannina, Ioannina, Greece. 1 INTRODUCTION TO EMOTION RECOGNITION Amit Konar and Anisha Halder Artificial Intelligence Laboratory, Department of Electronics and Telecommunication Engineering, Jadavpur University, Kolkata, India Aruna Chakraborty Department of Computer Science & Engineering, St. Thomas’ College of Engineering & Technology, Kolkata, India A pattern represents a characteristic set of attributes of an object by which it can be distinguished from other objects.

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