Integration of Multiple Sound Source Localization Results for Speaker Identification in Multiparty Dialogue System
Integration of Multiple Sound Source Localization Results for Speaker Identification in Multiparty Dialogue System
复制标题
集成多声源定位结果进行多方对话系统中说话人识别
DOI：
10.1007/978-1-4614-8280-2_14
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发表时间：
2012
期刊：
影响因子：
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通讯作者：
Satoshi Sato
中科院分区：
文献类型：
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作者：
Taichi Nakashima;Kazunori Komatani;Satoshi Sato
类人机器人在多方对话中回答问题时需要朝向人类参与者。在多方参与的情况下，参与者的某些位置很难从机器人定位，特别是当机器人只能使用自己的传感器时。我们提出了一种更准确地识别扬声器的方法，通过整合从两个机器人获得的多个声源定位结果：一个主要与参与者交谈，另一个也在必要时加入对话。我们放置它们，以便它们可以补偿彼此的本地化能力，然后集成它们的两个结果。我们的实验评估表明，使用两个机器人提高扬声器识别相比，只用一个机器人。此外，我们实现了我们的方法到人形机器人，并构建了一个演示系统。
Humanoid robots need to head toward human participants when answering to their questions in multiparty dialogues. Some positions of participants are difficult to localize from robots in multiparty situations, especially when the robots can only use their own sensors. We present a method for identifying the speaker more accurately by integrating the multiple sound source localization results obtained from two robots: one talking mainly with participants and the other also joining the conversation when necessary. We place them so that they can compensate for each other’s localization capabilities and then integrate their two results. Our experimental evaluation revealed that using two robots improved speaker identification compared with using only one robot. We furthermore implemented our method into humanoid robots and constructed a demo system.