Pre-Conference Talk by SHESHADRI Smitha | Conversational Localization: Indoor Human Localization through Intelligent Conversation

We propose a novel sensorless approach to indoor localization by leveraging natural language conversations with users, which we call conversational localization. To show the feasibility of conversational localization, we develop a proof-of-concept system that guides users to describe their surroundings in a chat and estimates their position based on the information they provide. We devised a modular architecture for our system with four modules. First, we construct an entity database with available image-based floor maps. Second, we enable the dynamic identification and scoring of information provided by users through our utterance processing module. Then, we implement a conversational agent that can intelligently strategize and guide the interaction to elicit localizationally valuable information from users. Finally, we employ visibility catchment area and line-of-sight heuristics to generate spatial estimates for the user's location. We conduct two user studies in designing and testing the system. We collect 800 natural language descriptions of unfamiliar indoor spaces in an online crowdsourcing study to learn the feasibility of extracting localizationally useful entities from user utterances. We then conduct a field study with 10 participants at 10 locations to evaluate the feasibility and performance of conversational localization. The results show that conversational localization can achieve within-10 meter localization accuracy at eight out of the ten study sites, showing the technique's utility for classes of indoor location-based services.

This is a Pre-Conference talk for The 2024 ACM International Joint Conference on Pervasive and Ubiquitous Computing (UbiComp / ISWC 2024).
 

Smitha SHESHADRI is a PhD candidate at Singapore Management University, working under the guidance of Professor Kotaro HARA. Her research focuses on natural language interfaces within the field of Human-Computer Interaction (HCI). Recently, she has been exploring the use of conversational interfaces in the domain of indoor localization, a novel application area aimed at creating a light-weight solution that does not rely on sensor architecture.