Augmenting the Social Presence of Interactive Characters Using Real-time Speech Recognition

Mizuki Yamano, Zhihao Song, Junichi Hoshino
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Abstract

Recently, in addition to games, interaction with real virtual agents has been used for job training. Furthermore, multimodal dialog using both voice and gesture recognition is used. However, there is a challenge with conventional batch processing speech recognition: it is difficult to make the virtual agent respond while the user is speaking. Therefore, in this study, we confirm the possibility of enhancing social presence by generating responses using real-time speech recognition in spoken dialog with characters. While the user speaks, by extracting keywords from the speech content in real-time, we generate the emotional response of the virtual agent. The experimental results demonstrate that our approach improves social presence compared with conventional spoken dialog.
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利用实时语音识别增强互动角色的社会存在感
最近,除了游戏之外,与真实虚拟代理的互动也被用于职业培训。此外,还使用了语音和手势识别的多模态对话。然而,传统的批处理语音识别存在一个挑战:当用户说话时,很难使虚拟代理做出响应。因此,在本研究中,我们确认了通过在与角色的口语对话中使用实时语音识别生成响应来增强社交存在的可能性。当用户说话时,我们通过实时从语音内容中提取关键词,生成虚拟代理的情绪反应。实验结果表明,与传统的口语对话相比,我们的方法提高了社交在场感。
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