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Emotion Recognition Using Speaker Cues

机译：使用说话者提示的情绪识别

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The focus of the current research is on emotion identification of a speaker using his/her cues. In this work, emotion identification depends on a two-stage framework. The first stage recognizes the speaker whose emotion is undetermined, while the second stage recognizes the unidentified emotion which was spoken by the speaker whose identity was recognized in the preceding stage. Our proposed architecture has been assessed on an Arabic Emirati-accented speech corpus expressed by fifteen Emirati speakers for every gender. As a classifier, Hidden Markov Model is exploited in this study. Our results show that the proposed two-stage framework is superior to the one-stage framework and the “state-of-the-art classifiers such as Gaussian Mixture Model, Support Vector Machine, and Vector Quantization”.
机译：当前研究的重点是利用说话者的提示识别说话者的情绪。在这项工作中，情绪识别取决于两个阶段的框架。第一阶段识别未确定情绪的说话者，而第二阶段识别未识别情绪的说话者在上一阶段识别身份的说话者所说的话。我们提议的体系结构已根据阿拉伯联合酋长国口音语料库进行了评估，该语料库由15位阿拉伯酋长国发言人针对每个性别表示。作为分类器，本研究利用了隐马尔可夫模型。我们的结果表明，提出的两阶段框架优于一阶段框架和“最新的分类器，例如高斯混合模型，支持向量机和向量量化”。

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