An End-to-End Conversational Style Matching Agent

We present an end-to-end voice-based conversational agent that is able to engage in naturalistic multi-turn dialogue and align with the interlocutor's conversational style. The system uses a series of deep neural network components for speech recognition, dialogue generation, prosodic analysis and speech synthesis to generate language and prosodic expression with qualities that match those of the user. We conducted a user study (N=30) in which participants talked with the agent for 15 to 20 minutes, resulting in over 8 hours of natural interaction data. Users with high consideration conversational styles reported the agent to be more trustworthy when it matched their conversational style. Whereas, users with high involvement conversational styles were indifferent. Finally, we provide design guidelines for multi-turn dialogue interactions using conversational style adaptation

Meetings and Meeting Modeling in Smart Environments

In this paper we survey our research on smart meeting rooms and its relevance for augmented reality meeting support and virtual reality generation of meetings in real time or off-line. The research reported here forms part of the European 5th and 6th framework programme projects multi-modal meeting manager (M4) and augmented multi-party interaction (AMI). Both projects aim at building a smart meeting environment that is able to collect multimodal captures of the activities and discussions in a meeting room, with the aim to use this information as input to tools that allow real-time support, browsing, retrieval and summarization of meetings. Our aim is to research (semantic) representations of what takes place during meetings in order to allow generation, e.g. in virtual reality, of meeting activities (discussions, presentations, voting, etc.). Being able to do so also allows us to look at tools that provide support during a meeting and at tools that allow those not able to be physically present during a meeting to take part in a virtual way. This may lead to situations where the differences between real meeting participants, human-controlled virtual participants and (semi-) autonomous virtual participants disappear

Generic dialogue modeling for multi-application dialogue systems

We present a novel approach to developing interfaces for multi-application dialogue systems. The targeted interfaces allow transparent switching between a large number of applications within one system. The approach, based on the Rapid Dialogue Prototyping Methodology (RDPM) and the Vector Space model techniques from Information Retrieval, is composed of three main steps: (1) producing finalized dia logue models for applications using the RDPM, (2) designing an application interaction hierarchy, and (3) navigating between the applications based on the user's application of interest

A system design for human factors studies of speech-enabled Web browsing

This paper describes the design of a system which will subsequently be used as the basis of a range of empirical studies aimed at discovering how best to harness speech recognition capabilities in multimodal multimedia computing. Initial work focuses on speech-enabled browsing of the World Wide Web, which was never designed for such use. System design is complete, and is being evaluated via usability testing

Gathering a corpus of multimodal computer-mediated meetings with focus on text and audio interaction

In this paper we describe the gathering of a corpus of synchronised speech and text interaction over the network. The data collection scenarios characterise audio meetings with a significant textual component. Unlike existing meeting corpora, the corpus described in this paper emphasises temporal relationships between speech and text media streams. This is achieved through detailed logging and time stamping of text editing operations, actions on shared user interface widgets and gesturing, as well as generation of speech activity profiles. A set of tools has been developed specifically for these purposes which can be used as a data collection platform for the development of meeting browsers. The data gathered to data consists of nearly 30 hours of recorded audio and time stamped editing operations and gestures