Emotion recognition and adaptation in spoken dialogue systems
Emotion recognition and adaptation in spoken dialogue systems
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DOI：
10.1007/s10772-010-9068-y
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发表时间：
2010-03
影响因子：
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通讯作者：
J. Pittermann;A. Pittermann;W. Minker
中科院分区：
文献类型：
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作者：
J. Pittermann;A. Pittermann;W. Minker
情绪状态在智能语音人机界面中的参与已经发展成为一个最新的研究领域。在本文中，我们描述了与自动语音识别联合运行的基于语音的情感识别器的增强和优化。我们认为，关于话语文本内容的知识可以提高对情感内容的识别。概述了实验设置后，我们展示了结果并展示了结合多个语音情感识别器的后处理算法的能力。对于对话管理，我们提出了一种随机方法，包括在组合对话情感模型中相互干扰的对话模型和情感模型。这些模型是根据对话语料库进行训练的，并被分配不同的权重因子，它们决定对话的过程。
The involvement of emotional states in intelligent spoken human-computer interfaces has evolved to a recent field of research. In this article we describe the enhancements and optimizations of a speech-based emotion recognizer jointly operating with automatic speech recognition. We argue that the knowledge about the textual content of an utterance can improve the recognition of the emotional content. Having outlined the experimental setup we present results and demonstrate the capability of a post-processing algorithm combining multiple speech-emotion recognizers. For the dialogue management we propose a stochastic approach comprising a dialogue model and an emotional model interfering with each other in a combined dialogue-emotion model. These models are trained from dialogue corpora and being assigned different weighting factors they determine the course of the dialogue.