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Hands-free speech recognition challenge for real-world speech dialogue systems

机译:现实世界中语音对话系统的免提语音识别挑战

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In this paper, we describe and review our recent development of hands-free speech dialogue system which is used for railway station guidance. In the application at the real railway station, robustness against reverberation and noise is the most essential issue for the dialogue system. To address the problem, we introduce two key techniques in our proposed hands-free system; (a) speech dialogue system construction with real speech database collection and language/acoustic model improvement, and (b) microphone array preprocessing using blind spatial subtraction array which can solve the reverberation-naiveness problem inherent in conventional microphone arrays. The experimental assessment of the proposed dialogue system reveals that our system can provide the recognition accuracy of more than 80% under realistic railway-station conditions.
机译:在本文中,我们描述并回顾了我们用于火车站导航的免提语音对话系统的最新发展。在实际火车站的应用中,抵抗混响和噪声的鲁棒性是对话系统最重要的问题。为了解决这个问题,我们在提议的免提系统中引入了两种关键技术: (a)具有真实语音数据库集合和语言/声学模型改进的语音对话系统构建,以及(b)使用盲空间减法阵列的麦克风阵列预处理,可以解决传统麦克风阵列固有的混响幼稚性问题。对所提出的对话系统的实验评估表明,我们的系统在实际的火车站条件下可以提供超过80%的识别精度。

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