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Emotion Expression for Affective Social Communication

机译:情感表达对情感社交的影响

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Human interaction with social networking services (SNS) is currently a very active research area. SNS posts, such as tweets, allow users to broadcast their ideas in short form of text, voice, or images, using mobile devices and computers. Text and speech enriched with emotions is one of the major ways of exchanging ideas, especially via telephony and SNS. By analyzing a voice stream using a Hidden Markov Model (HMM) and Log Frequency Cepstral Coefficients (LFPC) based system, different emotions can be recognized. Using a simple Java client, recognized emotions can be delivered to a server as an index. A mobile client can then retrieve the emotion and display it through colored icons. Each emotion is mapped to a particular color, as it is natural to use colors to represent various expressions. Not only colors, we also use avatar animation models in different environments for the expression of different emotions.
机译:与社交网络服务(SNS)的人机交互目前是一个非常活跃的研究领域。 SNS帖子(例如推文)允许用户使用移动设备和计算机以短文本,语音或图像形式广播其想法。充满情感的文本和语音是交换想法的主要方法之一,尤其是通过电话和SNS进行交换。通过使用基于隐马尔可夫模型(HMM)和对数频率倒谱系数(LFPC)的系统分析语音流,可以识别不同的情绪。使用简单的Java客户端,可以将识别出的情绪作为索引传递到服务器。然后,移动客户端可以检索情感并通过彩色图标显示它。每种情感都映射到一种特定的颜色,因为使用颜色表示各种表情很自然。不仅是颜色,我们还在不同的环境中使用头像动画模型来表达不同的情感。

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