This paper describes a spoken dialogue system for accommodating a user's information behaviors with various levels of information need. Our system, given a set of same-topic news articles, compiles a utterance plan that consists of a primary plan for delivering main news content, and the associated subsidiary plans for supplementing the main content. A primary plan is generated by applying text summarization and style conversion techniques. The subsidiary plans are compiled by considering potential user/system interactions. To make this mechanism work, we first classified user's possible passive/active behaviors, and then designed the corresponding system actions. We empirically confirmed that our system was able to deliver the news content smoothly while dynamically adapting to the change of user's intention levels. The smoothness of a conversation can be attributed to the pre-compiled utterance plan.

No abstract

We propose a conversational speech synthesis system in which the prosodic features of each utterance are controlled throughout the entire input text. We have developed a "news-telling system," which delivered news articles through spoken language. The speech synthesis system for the news-telling should be able to highlight utterances containing noteworthy information in the article with a particular way of speaking so as to impress them on the users. To achieve this, we introduced role and position features of the individual utterances in the article into the control parameters for prosody generation throughout the text. We defined three categories for the role feature: a nucleus (which is assigned to the utterance including the noteworthy information), a front satellite (which precedes the nucleus) and a rear satellite (which follows the nucleus). We investigated how the prosodic features differed depending on the role and position features through an analysis of news-telling speech data uttered by a voice actress. We designed the speech synthesis system on the basis of a deep neural network having the role and position features added to its input layer. Objective and subjective evaluation results showed that introducing those features was effective in the speech synthesis for the information delivering.

keywords: conversational speech synthesis, DNN-based speech synthesis, paragraph-based speech synthesis, pause length estimation, prominence SummaryWe have been developing a speech-based "news-delivery system", which can transmit news contents via spoken dialogues. In such a system, a speech synthesis sub system that can flexibly adjust the prosodic features in utterances is highly vital: the system should be able to highlight spoken phrases containing noteworthy information in an article; it should also provide properly controlled pauses between utterances to facilitate user's interactive reactions including questions. To achieve these goals, we have decided to incorporate the position of the utterance in the paragraph and the role of the utterance in the discourse structure into the bundle of features for speech synthesis. These features were found to be crucially important in fulfilling the above-mentioned requirements for the spoken utterances by the thorough investigation into the news-telling speech data uttered by a voice actress. Specifically, these features dictate the importance of information carried by spoken phrases, and hence should be effectively utilized in synthesizing prosodically adequate utterances. Based on these investigations, we devised a deep neural network-based speech synthesis model that takes as input the role and position features. In addition, we designed a neural network model that can estimate an adequate pause length between utterances. Experimental results showed that by adding these features to the input, it becomes more proper speech for information delivery. Furthermore, we confirmed that by inserting pauses properly, it becomes easier for users to ask questions during system utterances. * 1 http://www.apple.com/jp/ios/siri/ * 2 https://www.softbank.jp/robot/consumer/ products/ 15, Yoshino 15][ 18a]