A study on content summarization for large spoken documents and content retrieval through spoken dialogue

为了开发面向开放域语音文档检索的精确大词汇量连续语音识别系统，提出了一种并行使用两种搜索算法实现高效准确解码的方法。我们对这种新的搜索算法进行了评估，并在不增加计算成本的情况下获得了显著的识别性能改进。我们还提出了将机器学习技术应用于多个LVCSR模型输出组合的任务。该方法优于ROVER等投票方案，特别是在大多数参与模型不可靠的情况下。通过使用该技术，我们执行了一个语音驱动的Web检索任务，提高了语音查询的语音识别精度，进而提高了语音驱动Web检索的检索精度。为此，我们研究了语言表面信息与人的结果之间的关系，获得了有用的表面语言信息。接下来，我们根据这些信息总结口语讲座，并与人类的结果进行比较。因此，我们获得了与人类结果相当的更好的f测量值和k值。我们开发了一个便携式语音识别模块和一个语音对话系统中的翻译模块。此外，我们还开发了对话策略设计工具，并将其应用于富士山观光导游检索、文献检索和酒店预订检索中，验证了其实用性。

To develop an accurate large vocabulary continuous speech recognition system for spoken document retrieval in open domain, we proposed a search method using two search algorithms in parallel to achieve efficient and accurate decoding. We evaluated this new search algorithm and obtained significant improvement of recognition performance without severe increase of computational cost We also proposed to apply machine learning techniques to the task of combining outputs of multiple LVCSR models. The proposed technique had advantages over that by voting schemes such as ROVER, especially when the majority of participating models are not reliable. By using this technique, we performed a speech-driven Web retrieval task and improved speech recognition accuracy of spoken queries and then improved retrieval accuracy in speech driven Web retrieval We tried the summarization of spoken lectures. For this purpose, we investigated relations between linguistic surface information and human's results, and we obtained useful surface linguistic information. Next, we summarized spoken lectures based on this information, and compared them with human's results. As a result, we obtained a better F-measure and k-value comparable with human's results. We have developed a portable speech recognition module and an interpreter module in a spoken dialogue system. Furthermore, we also developed a dialogue strategy design tool, applied it to Mt.Fuji sightseeing guidance retrieval, literature retrieval and hotel reservation retrieval and then confirmed the usefulness.