Evaluation of natural language understanding based speech dialog interface's effectiveness regarding car navigation system usability performance

Abstract

Recently, new cell phone services enable taking input by speaking to a quasi-agent using highly accurate speech recognition technologies. However, there are two problems when equipping a vehicle with these technologies. First, we do not understand yet the effect on driver’s usability performance of a car navigation system equipped with spoken dialogue interface. Second, the corresponding design techniques to obtain sufficiently good navigation results has not yet been determined. In this study, we first discuss problems involving speech recognition technologies and the types of speech interface used in this study. Second, we experimentally compare in pseudo-driving conditions the effect on driver’s physiology of various speech user interfaces: the Command Input (CI) interface, the Natural Language Understanding (NLU) interface, and the NLU/Spoken Dialogue Management (SDM) interface. According to the analysis of physiological signals, parasympathetic nervous system activity index value was higher when using the NLU/SDM interface than when using the CI interface. Furthermore, both subjective assessment result and time satisfaction degree of NLU/SDM interface were higher than others. Therefore, we can conclude that the NLU/SDM-type interface has better usability performance.

Natural language understanding and interaction engine oriented to human-computer interaction based on neural network

“…It can solve some problems in a specific field according to the needs of users, and complete task-based instructions in the form of dialogue. In the process of traditional task-based dialogue systems, the most important module is natural/speech language understanding, which analyzes the user's unstructured natural language input into structured semantic representations [7][8].…”