works on

From the 1 of 13 linked papers with an AI index.

activity
20242026
collaborators

13 papers

cs.CL2026

On the Structure of Address in Multi-Party Dialogue: From Discrete Labels to Continuous Levels

Taiga Mori, Koji Inoue, Divesh Lala +1

In multi-party dialogues between a dialogue system and multiple users, identifying to whom an utterance is addressed is a key challenge. Prior work has typically treated addressee…

cs.HC2026

Real-time Generation of Listener Nodding via Prediction of Kinematic Parameters for Avatar Dialogue Systems

Kazushi Kato, Koji Inoue, Taiga Mori +2

The paper introduces a lightweight, real-time model that predicts both the timing and motion parameters of listener nodding for conversational avatars, using a dyadic attention net…

cs.CL2025

Multilingual and Continuous Backchannel Prediction: A Cross-lingual Study

Koji Inoue, Mikey Elmers, Yahui Fu +5

We present a multilingual, continuous backchannel prediction model for Japanese, English, and Chinese, and use it to investigate cross-linguistic timing behavior. The model is Tran…

cs.CL2025

Triadic Multi-party Voice Activity Projection for Turn-taking in Spoken Dialogue Systems

Mikey Elmers, Koji Inoue, Divesh Lala +1

Turn-taking is a fundamental component of spoken dialogue, however conventional studies mostly involve dyadic settings. This work focuses on applying voice activity projection (VAP…

cs.RO2025

Why Report Failed Interactions With Robots?! Towards Vignette-based Interaction Quality

Agnes Axelsson, Merle Reimann, Ronald Cumbal +2

Although the quality of human-robot interactions has improved with the advent of LLMs, there are still various factors that cause systems to be sub-optimal when compared to human-h…

cs.HC2025

Real-time Generation of Various Types of Nodding for Avatar Attentive Listening System

Kazushi Kato, Koji Inoue, Divesh Lala +2

In human dialogue, nonverbal information such as nodding and facial expressions is as crucial as verbal information, and spoken dialogue systems are also expected to express such n…