  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.
