A conversational agent that evaluates user experience in a virtual reality game

Treballs Finals de Grau d'Enginyeria Informàtica, Facultat de Matemàtiques, Universitat de Barcelona, Any: 2022, Director: Changhao Wang[en] In the last few years, both chatbots and Virtual Reality games have become a hot topic of discussion. On the one hand, chatbots have been used in recent years, especially for customer service, and on the other hand, VR is being promoted thanks to the commitment of large companies such as Facebook and also thanks to lower equipment costs. However, there has been little discussion on the use of the conversational agent in Virtual Reality games to gather user opinions. The main objective of this project focuses on the creation of a conversational agent, capable of interacting with the user through voice and text, and then integrate it into a Virtual Reality game to evaluate user experience in that immersive environment. Specifically, to pave the way of using conversational interaction in a Virtual Reality environment to improve the efficacy of the evaluation process. We design and create a survey agent using Rasa open source platform. In order to evaluate UX, we use the Game Experience Questionnaire. Finally, we integrate the Rasa agent into a game scene in Unity that works in Virtual Reality environment

Attention-Based End-to-End Speech Recognition on Voice Search

Recently, there has been a growing interest in end-to-end speech recognition that directly transcribes speech to text without any predefined alignments. In this paper, we explore the use of attention-based encoder-decoder model for Mandarin speech recognition on a voice search task. Previous attempts have shown that applying attention-based encoder-decoder to Mandarin speech recognition was quite difficult due to the logographic orthography of Mandarin, the large vocabulary and the conditional dependency of the attention model. In this paper, we use character embedding to deal with the large vocabulary. Several tricks are used for effective model training, including L2 regularization, Gaussian weight noise and frame skipping. We compare two attention mechanisms and use attention smoothing to cover long context in the attention model. Taken together, these tricks allow us to finally achieve a character error rate (CER) of 3.58% and a sentence error rate (SER) of 7.43% on the MiTV voice search dataset. While together with a trigram language model, CER and SER reach 2.81% and 5.77%, respectively

Lifetimes of weakly bound heavy-Rydberg ion-pair states formed through Rydberg atom collisions with attaching targets

The formation of K+···Cl- heavy-Rydberg ion-pair states through dissociative electron attachment in K(np)/CCl4 collisions is investigated. The product ion-pair states are detected directly by electric field-induced dissociation. A Monte Carlo collision code is used to analyze the results that models both the initial Rydberg electron attachment and the subsequent evolution of the ion pairs. The data and the calculations demonstrate the production of long-lived bound K+···Cl- heavy-Rydberg ion pairs. They also suggest that collinear collisions can generate heavy-Rydberg states of low angular momentum

Berberine Improves Glucose Homeostasis in Streptozotocin-Induced Diabetic Rats in Association with Multiple Factors of Insulin Resistance

The present study was carried out to determine the effect of berberine on glucose homeostasis and several biomarkers associated with insulin sensitivity in male Wistar rats with intraperitoneal injection of streptozotocin (STZ)-induced diabetes. Rats with fasting blood glucose 16.7 mmol/L after 2 weeks of STZ injection were divided into two groups. One group was used as the diabetic control and another treated by gavage feeding with 100 mg/kg/d of berberine in water containing 0.5% carboxymethyl cellulose. A group of rats without receiving STZ was used as the normal control. After 7 weeks, berberine supplementation moderately but significantly lowered fasting blood glucose levels and improved oral glucose tolerance. Berberine lowered plasma free fatty acids and C-reactive protein levels without affecting plasma insulin levels. Diabetic rats treated with berberine showed significantly lower plasma triacylglycerol and cholesterol levels. Furthermore, berberine inhibited dipeptidyl peptidase-4 and protein tyrosine phosphatase-1B activities. In conclusion, berberine showed a dramatic effect of lowering blood cholesterol and triacylglycerols and improved moderately glucose homeostasis in STZ-induced diabetic rats in association with multiple factors related to insulin resistance

A Coarse-to-Fine Framework for Dual-Arm Manipulation of Deformable Linear Objects with Whole-Body Obstacle Avoidance

Manipulating deformable linear objects (DLOs) to achieve desired shapes in constrained environments with obstacles is a meaningful but challenging tasks. Global planning is necessary for such a highly-constrained task; however, accurate models of DLOs required by planners are difficult to obtain owing to their deformable nature, and the inevitable modeling errors significantly affect the planning results, probably resulting in task failure if the robot simply executes the planned path in an open-loop manner. In this paper, we propose a coarse-to-fine framework to combine global planning and local control for dual-arm manipulation of DLOs, capable of precisely achieving desired configurations and avoiding potential collisions between the DLO, robot, and obstacles. Specifically, the global planner refers to a simple yet effective DLO energy model and computes a coarse path to guarantee the feasibility of the task; then the local controller follows that path as guidance and further shapes it with closed-loop feedback to compensate for the planning errors and guarantee the accuracy of the task. Both simulations and real-world experiments demonstrate that our framework can robustly achieve desired DLO configurations in constrained environments with imprecise DLO models. which may not be reliably achieved by only planning or control