情绪识别调节智能系统的行为

2013 IEEE International Symposium on Broadband Multimedia Systems and Broadcasting (BMSB) Pub Date : 2013-12-09 DOI:10.1109/ISM.2013.72

A. Smailagic, D. Siewiorek, A. Rudnicky, Sandeep Nallan Chakravarthula, Anshuman Kar, Nivedita Jagdale, Saksham Gautam, Rohit Vijayaraghavan, S. Jagtap

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引用次数: 4

摘要

本文提出了一种基于音频的情绪识别系统，该系统能够实时地将情绪分为愤怒、恐惧、快乐、中性、悲伤或厌恶。我们使用虚拟教练作为情感识别如何用于调节智能系统行为的应用示例。介绍了一种新的最小误差特征去除机制，以减少带宽和提高我们的情绪识别系统的准确性。使用了两阶段分层分类方法以及“一对全”(One-Against-All, OAA)框架。通过修剪特征集并使用支持向量机(svm)进行分类，使用OAA方法获得了82.07%的平均准确率，使用两阶段分层方法获得了87.70%的平均准确率。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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Emotion Recognition Modulating the Behavior of Intelligent Systems

The paper presents an audio-based emotion recognition system that is able to classify emotions as anger, fear, happy, neutral, sadness or disgust in real time. We use the virtual coach as an application example of how emotion recognition can be used to modulate intelligent systems' behavior. A novel minimum-error feature removal mechanism to reduce bandwidth and increase accuracy of our emotion recognition system has been introduced. A two-stage hierarchical classification approach along with a One-Against-All (OAA) framework are used. We obtained an average accuracy of 82.07% using the OAA approach, and 87.70% with a two-stage hierarchical approach, by pruning the feature set and using Support Vector Machines (SVMs) for classification.

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来源期刊

2013 IEEE International Symposium on Broadband Multimedia Systems and Broadcasting (BMSB)

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