Natural Language Understanding: Methodological Conceptualization

This article contains the results of a theoretical analysis of the phenomenon of natural language understanding (NLU), as a methodological problem. The combination of structural-ontological and informational-psychological approaches provided an opportunity to describe the subject matter field of NLU, as a composite function of the mind, which systemically combines the verbal and discursive structural layers. In particular, the idea of NLU is presented, on the one hand, as the relation between the discourse of a specific speech message and the meta-discourse of a language, in turn, activated by the need-motivational factors. On the other hand, it is conceptualized as a process with a specific structure of information metabolism, the study of which implies the necessity to differentiate the affective (emotional) and need-motivational influences on the NLU, as well as to take into account their interaction. At the same time, the hypothesis about the influence of needs on NLU under the scenario similar to the pattern of Yerkes-Dodson is argued. And the theoretical conclusion that emotions fulfill the function of the operator of the structural features of the information metabolism of NLU is substantiated. Thus, depending on the modality of emotions in the process of NLU, it was proposed to distinguish two scenarios for the implementation of information metabolism - reduction and synthetic. The argument in favor of the conclusion about the productive and constitutive role of emotions in the process of NLU is also given

Voice Interaction for Augmented Reality Navigation Interfaces with Natural Language Understanding

Voice interaction with natural language understanding (NLU) has been extensively explored in desktop computers, handheld devices, and human-robot interaction. However, there is limited research into voice interaction with NLU in augmented reality (AR). There are benefits of using voice interaction in AR, such as high naturalness and being hands-free. In this project, we introduce VOARLA, an NLU-powered AR voice interface, which navigate courier driver delivery a package. A user study was completed to evaluate VOARLA against an AR voice interface without NLU to investigate the effectiveness of NLU in the navigation interface in AR. We evaluated from three aspects: accuracy, productivity, and commands learning curve. Results found that using NLU in AR increases the accuracy of the interface by 15%. However, higher accuracy did not correlate to an increase in productivity. Results suggest that NLU helped users remember the commands on the first run when they were unfamiliar with the system. This suggests that using NLU in an AR hands-free application can make the learning curve easier for new users

Introducing the NLU Showroom: A NLU Demonstrator for the German Language

We present the NLU Showroom, a platform for interactively demonstrating the functionality of natural language understanding models with easy to use visual interfaces. The NLU Showroom focuses primarily on the German language, as not many German NLU resources exist. However, it also serves corresponding English models to reach a broader audience. With the NLU Showroom we demonstrate and compare the capabilities and limitations of a variety of NLP/NLU models. The four initial demonstrators include a) a comparison on how different word representations capture semantic similarity b) a comparison on how different sentence representations interpret sentence similarity c) a showcase on analyzing reviews with NLU d) a showcase on finding links between entities. The NLU Showroom is build on state-of-the-art architectures for model serving and data processing. It targets a broad audience, from newbies to researchers but puts a focus on putting the presented models in the context of industrial applications