Studying Mutual Phonetic Influence with a Web-Based Spoken Dialogue System

This paper presents a study on mutual speech variation influences in a human-computer setting. The study highlights behavioral patterns in data collected as part of a shadowing experiment, and is performed using a novel end-to-end platform for studying phonetic variation in dialogue. It includes a spoken dialogue system capable of detecting and tracking the state of phonetic features in the user's speech and adapting accordingly. It provides visual and numeric representations of the changes in real time, offering a high degree of customization, and can be used for simulating or reproducing speech variation scenarios. The replicated experiment presented in this paper along with the analysis of the relationship between the human and non-human interlocutors lays the groundwork for a spoken dialogue system with personalized speaking style, which we expect will improve the naturalness and efficiency of human-computer interaction.