A Survey on Dialogue Systems: Recent Advances and New Frontiers

Dialogue systems have attracted more and more attention. Recent advances on dialogue systems are overwhelmingly contributed by deep learning techniques, which have been employed to enhance a wide range of big data applications such as computer vision, natural language processing, and recommender systems. For dialogue systems, deep learning can leverage a massive amount of data to learn meaningful feature representations and response generation strategies, while requiring a minimum amount of hand-crafting. In this article, we give an overview to these recent advances on dialogue systems from various perspectives and discuss some possible research directions. In particular, we generally divide existing dialogue systems into task-oriented and non-task-oriented models, then detail how deep learning techniques help them with representative algorithms and finally discuss some appealing research directions that can bring the dialogue system research into a new frontier.Comment: 13 pages. arXiv admin note: text overlap with arXiv:1703.01008 by other author

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

SketchyGAN: Towards Diverse and Realistic Sketch to Image Synthesis

Synthesizing realistic images from human drawn sketches is a challenging problem in computer graphics and vision. Existing approaches either need exact edge maps, or rely on retrieval of existing photographs. In this work, we propose a novel Generative Adversarial Network (GAN) approach that synthesizes plausible images from 50 categories including motorcycles, horses and couches. We demonstrate a data augmentation technique for sketches which is fully automatic, and we show that the augmented data is helpful to our task. We introduce a new network building block suitable for both the generator and discriminator which improves the information flow by injecting the input image at multiple scales. Compared to state-of-the-art image translation methods, our approach generates more realistic images and achieves significantly higher Inception Scores.Comment: Accepted to CVPR 201

Reusable Agena study. Volume 1: Executive summary

The shuttle Agena upper stage interim tug concept is based on a building block approach. These building block concepts are extensions of existing ascent Agena configurations. Several current improvements, have been used in developing the shuttle/Agena upper stage concepts. High-density acid is used as the Agena upper stage oxidizer. The baffled injector is used in the main engine. The DF-224 is a fourth generation computer currently in development and will be flight proven in the near future. The Agena upper stage building block concept uses the current Agena as a baseline, adds an 8.5-inch (21.6 cm) extension to the fuel tank for optimum mixture ratio, uses monomethyl hydrazine as fuel, exchanges a 150:1 nozzle extension for the existing 45:1, exchanges an Autonetics DF-224 for the existing Honeywell computer, and adds a star sensor for guidance update. These modifications to the current Agena provide a 5-foot (1.52m) diameter shuttle/Agena upper stage that will fly all Vandenberg Air Force Base missions in the reusable mode without resorting to a kick motor. The delta V velocity of the Agena is increased by use of a strap-on propellant tank option. This option provides a shuttle/Agena upper stage with the capability to place almost 3900 pounds (1769 kg) into geosynchronous orbit (24 hour period) without the aid of kick motors