具有可扩展性和鲁棒性的多域语音对话系统

Kazunori Komatani, Naoyuki Kanda, Mikio Nakano, K. Nakadai, H. Tsujino, T. Ogata, HIroshi G. Okuno
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引用次数: 50

摘要

我们开发了一个多域语音对话系统,可以处理跨多个域的用户请求。这样的系统需要满足两个要求:可扩展性和对语音识别错误的鲁棒性。为了允许独立于其他域的域的修改和添加,需要可扩展性。对语音识别错误的鲁棒性是必要的,因为这种错误在语音识别中是不可避免的。但是,即使系统的输入是错误的,系统也应该表现得适当。该系统采用可扩展的体系结构,具有鲁棒性和可扩展性强的领域选择方法。领域的选择基于三个选择:(I)前一个领域,(II)识别分数最高的可接受语音识别结果的领域,(III)其他领域。在我们新引入的第三个选择中,我们的系统可以防止对话持续被困在错误的域中。实验结果表明,与传统方法相比,我们的方法将域选择误差降低了18.3%。
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Multi-Domain Spoken Dialogue System with Extensibility and Robustness against Speech Recognition Errors
We developed a multi-domain spoken dialogue system that can handle user requests across multiple domains. Such systems need to satisfy two requirements: extensibility and robustness against speech recognition errors. Extensibility is required to allow for the modification and addition of domains independent of other domains. Robustness against speech recognition errors is required because such errors are inevitable in speech recognition. However, the systems should still behave appropriately, even when their inputs are erroneous. Our system was constructed on an extensible architecture and is equipped with a robust and extensible domain selection method. Domain selection was based on three choices: (I) the previous domain, (II) the domain in which the speech recognition result can be accepted with the highest recognition score, and (III) other domains. With the third choice we newly introduced, our system can prevent dialogues from continuously being stuck in an erroneous domain. Our experimental results, obtained with 10 subjects, showed that our method reduced the domain selection errors by 18.3%, compared to a conventional method.
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