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首页> 外文会议>International conference on affective computing and intelligent interaction;ACII 2011 >Audio-Based Emotion Recognition from Natural Conversations Based on Co-Occurrence Matrix and Frequency Domain Energy Distribution Features
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Audio-Based Emotion Recognition from Natural Conversations Based on Co-Occurrence Matrix and Frequency Domain Energy Distribution Features

机译：基于共现矩阵和频域能量分布特征的自然对话中基于音频的情感识别

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摘要

Emotion recognition from natural speech is a very challenging problem. The audio sub-challenge represents an initial step towards building an efficient audio-visual based emotion recognition system that can detect emotions for real life applications (i.e. human-machine interaction and/or communication). The SEMAINE database, which consists of emotionally colored conversations, is used as the benchmark database. This paper presents our emotion recognition system from speech information in terms of positiveegative valence, and high and low arousal, expectancy and power. We introduce a new set of features including Co-Occurrence matrix based features as well as frequency domain energy distribution based features. Comparisons between well-known prosodic and spectral features and the new features are presented. Classification using the proposed features has shown promising results compared to the classical features on both the development and test data sets.
机译：自然语音的情感识别是一个非常具有挑战性的问题。音频子挑战表示朝着建立有效的基于视听的情感识别系统迈出的第一步，该情感识别系统可以检测现实生活中的情感（即人机交互和/或通信）。 SEMAINE数据库（由充满情感的对话组成）用作基准数据库。本文从语音信息的正/负价，高低唤醒，期望和力量等方面介绍了我们的语音识别系统。我们介绍了一组新功能，包括基于共现矩阵的功能以及基于频域能量分布的功能。介绍了著名的韵律和频谱特征与新特征之间的比较。与开发和测试数据集上的经典特征相比，使用提出的特征进行分类已显示出令人鼓舞的结果。

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