Bimodal Emotion Recognition by Man and Machine
نویسندگان
چکیده
In this paper, we report preliminary results of recognizing emotions using both speech and video by machine. We applied automatic feature analysis and extraction algorithms to the same data used by De Silva et al. 5] in their human subjective studies. We compare machine recognition results to human performances in three tests:(1) video only, (2) audio only, (3) combined audio and video. In machine-assisted analyses, we found these two modalities to be complementary. Emotion categories that have similar features in one modality have very diierent features in the other modality. By using both, we show it is possible to achieve higher recognition rates than either modality alone.
منابع مشابه
A Database for Automatic Persian Speech Emotion Recognition: Collection, Processing and Evaluation
Abstract Recent developments in robotics automation have motivated researchers to improve the efficiency of interactive systems by making a natural man-machine interaction. Since speech is the most popular method of communication, recognizing human emotions from speech signal becomes a challenging research topic known as Speech Emotion Recognition (SER). In this study, we propose a Persian em...
متن کاملClassification of emotional speech using spectral pattern features
Speech Emotion Recognition (SER) is a new and challenging research area with a wide range of applications in man-machine interactions. The aim of a SER system is to recognize human emotion by analyzing the acoustics of speech sound. In this study, we propose Spectral Pattern features (SPs) and Harmonic Energy features (HEs) for emotion recognition. These features extracted from the spectrogram ...
متن کاملA New Information Fusion Method for Bimodal Robotic Emotion Recognition
Emotion recognition has become a popular area in human-robot interaction research. Through recognizing facial expressions, a robot can interact with a person in a more friendly manner. In this paper, we proposed a bimodal emotion recognition system by combining image and speech signals. A novel probabilistic strategy has been studied for a support vector machine (SVM)-based classification desig...
متن کاملNoise Analysis in Audio-Visual Emotion Recognition
This paper describes the use of a decision-based fusion framework to infer emotion from audiovisual feeds, and investigates the effect of noise on the fusion system. Facial expression features are constructed from linear binary patterns, and are processed independently of the prosodic features. A linear support vector machine is used for the fusion of the two channels. The results show that the...
متن کاملA hybrid EEG-based emotion recognition approach using Wavelet Convolutional Neural Networks (WCNN) and support vector machine
Nowadays, deep learning and convolutional neural networks (CNNs) have become widespread tools in many biomedical engineering studies. CNN is an end-to-end tool which makes processing procedure integrated, but in some situations, this processing tool requires to be fused with machine learning methods to be more accurate. In this paper, a hybrid approach based on deep features extracted from Wave...
متن کامل