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Carlos Toshinori Ishi

10 accepted papers

2024

Is It Possible to Recognize a Speaker Without Listening? Unraveling Conversation Dynamics in Multi-Party Interactions Using Continuous Eye Gaze

RA-L 2024

This study investigates the feasibility of understanding conversation dynamics in multi-party interactions without relying on auditory cues, focusing on continuous eye gaze as a key non-verbal communication modality. Without converting gaze into binary features, the study aims to explore the richnes

Cited by 2SourceScholar
2023

HAG: Hierarchical Attention with Graph Network for Dialogue Act Classification in Conversation

ICASSP 2023accepted

The prediction of dialogue acts (DA) labels on utterance-level in conversations can be treated as a sequence labeling problem, which requires context- and speaker-aware semantic comprehension, especially for Japanese. In this study, we pro-posed a hierarchical attention with the graph neural network…

Cited by 0SourceScholar
2023

Recognizing Real-World Intentions using A Multimodal Deep Learning Approach with Spatial-Temporal Graph Convolutional Networks

IROS 2023poster

Identifying intentions is a critical task for comprehending the actions of others, anticipating their future behavior, and making informed decisions. However, it is challenging to recognize intentions due to the uncertainty of future human activities and the complex influence factors. In this work,…

Cited by 0SourceScholar
2021

Advocating Attitudinal Change Through Android Robot's Intention-Based Expressive Behaviors: Toward WHO COVID-19 Guidelines Adherence

RA-L 2021

Motivated by the fact that some human emotional expressions promote affiliating functions such as signaling, social change, and support, all of which have been established as providing social benefits, we investigated how these behaviors can be extended to Human-Robot Interaction (HRI) scenarios. We

Cited by 7SourceScholar
2021

Enabling Robots to Distinguish Between Aggressive and Joking Attitudes

RA-L 2021

During a conversation, the meaning of an utterance may drastically change depending on the attitude of the speaker. For example, offensive words may be used “seriously” to threaten or “jokingly” to tease. However, robots do not have yet the capacity to understand such nuance. Therefore, we have deve

Cited by 7SourceScholar
2021

MAEC: Multi-Instance Learning with an Adversarial Auto-Encoder-Based Classifier for Speech Emotion Recognition

ICASSP 2021accepted

In this paper, we propose an adversarial auto-encoder-based classifier, which can regularize the distribution of latent representation to smooth the boundaries among categories. Moreover, we adopt multi-instance learning by dividing speech into a bag of segments to capture the most salient moments f…

Cited by 0SourceScholar
2021

Using an Android Robot to Improve Social Connectedness by Sharing Recent Experiences of Group Members in Human-Robot Conversations

RA-L 2021

Social connectedness is vital for developing group cohesion and strengthening belongingness. However, with the accelerating pace of modern life, people have fewer opportunities to participate in group-building activities. Furthermore, owing to the teleworking and quarantine requirements necessitated

Cited by 20SourceScholar
2020

Person-Directed Pointing Gestures and Inter-Personal Relationship: Expression of Politeness to Friendliness by Android Robots

RA-L 2020

Pointing at a person is usually deemed to be impolite. However, several different forms of person-directed pointing gestures commonly appear in casual dialogue interactions. In this study, we first analyzed pointing gestures in human-human dialogue interactions and observed different trends in the u

Cited by 6SourceScholar
2018

A Speech-Driven Hand Gesture Generation Method and Evaluation in Android Robots

RA-L 2018

Hand gestures commonly occur in daily dialogue interactions, and have important functions in communication. We first analyzed a multimodal human-human dialogue data and found relations between the occurrence of hand gestures and dialogue act categories. We also conducted a clustering analysis on ges

Cited by 56SourceScholar
2017

Motion Analysis in Vocalized Surprise Expressions and Motion Generation in Android Robots

RA-L 2017

Surprise expressions often occur in dialogue interactions, and they are often accompanied by verbal interjectional utterances. We are dealing with the challenge of generating natural human-like motions during speech in android robots that have a highly human-like appearance. In this study, we focus

Cited by 21SourceScholar