Hye-Jin Min

Emotion Interaction System for a Service Robot

This paper introduces an emotion interaction system for a service robot. The purpose of emotion interaction systems in service robots is to make people feel that the robot is not a mere machine, but reliable living assistant in the home. The emotion interaction system is composed of the emotion recognition, generation, and expression systems. A users emotion is recognized by multi-modality, such as voice, dialogue, and touch. The robots emotion is generated according to a psychological theory about emotion: OCC (Ortony, Clore, and Collins) model, which focuses on the users emotional state and the information about environment and the robot itself. The generated emotion is expressed by facial expression, gesture, and the musical sound of the robot. Because the proposed system is composed of all the three components that are necessary for a full emotional interaction cycle, it can be implemented in the real robot system and be tested. Even though the multi- modality in emotion recognition and expression is still in its rudimentary stages, the proposed system is shown to be extremely useful in service robot applications. Furthermore, the proposed framework can be a cornerstone for the design of emotion interaction and generation systems for robots.

Toward finer-grained sentiment identification in product reviews through linguistic and ontological analyses

We propose categories of finer-grained polarity for a more effective aspect-based sentiment summary, and describe linguistic and ontological clues that may affect such fine-grained polarity. We argue that relevance for satisfaction, contrastive weight clues, and certain adver-bials work to affect the polarity, as evidenced by the statistical analysis.

Enhancing readability of web documents by text augmentation for deaf people

Deaf people have particular difficulty in understanding text-based web documents because their mother language, or sign language, is essentially visually oriented. To enhance the readability of text-based web documents for deaf people, we propose a news display system that converts complex sentences in news articles into simple sentences and presents the relations among them with a graphical representation. In particular, we focus on the tasks of 1) identifying subordinate and embedded clauses in complex sentences, 2) relocating them for better readability and 3) displaying the relations among the clauses with the graphical representation. The results of our evaluation show that the proposed system does simplify complex sentences in news articles effectively while maintaining their intended meaning, suggesting that our system can be used in practice to help deaf people to access textual information.

Representing Emotions with Linguistic Acuity

For a robot to make effective and friendly interaction with human users, it is important to keep track of emotional changes in utterance properly. Emotions have traditionally been characterized by intuitive but atomic categories or as points in evaluation-activity dimensions. However, this characterization falls short of capturing subtle emotional changes either in narration or in text, where the vast majority of information is presented with a host of linguistic constructions that convey emotional information. We propose a novel representation scheme for emotions, so that such important features as duration, target and intensity can also be treated as first-class citizens and systematically accounted for. We argue that it is with this new mode of representation that the subtlety of the emotional flow in utterance can be properly addressed. We use this representation to encode the emotional states and intentions of characters in the drama scripts for soap opera and describe how it is utilized in conjunction with parsing for lexicalized grammars.

Speaker-TTS voice mapping towards natural and characteristic robot storytelling

Robot storytelling has the potential for its practical use in various domains such as entertainment, education, and rehabilitation. However, relying on human-recorded voices for natural storytelling is costly, and automation with text-to-speech systems is not readily applicable due to the difficulty of reflecting the full nature of stories in TTS systems. In this paper, we address the problem of automating robot storytelling with a particular focus on two issues: speaker identification and speaker-TTS voice mapping. We first conduct text analysis with rich linguistic clues to identify speakers from a given textual story. We then consider the task of speaker-TTS voice mapping as the graph coloring problem and propose effective algorithms for assigning voices to speakers given a limited number of TTS voices. Finally, we perform a user experiment on validating the usefulness of our method. The results demonstrate that our system significantly outperforms baseline systems and is also more acceptable to users.

Emotional Exchange of a Socially Interactive Robot

This paper presents an emotional exchange framework for a socially interactive robot. The purpose of emotional exchange in social interaction between a robot and people is to make people feel that the robot is a believable living assistant, not a mere machine for information translation. Our emotional exchange framework is composed of the emotion recognition, generation, and expression systems. A users emotion is recognized by multi-modality such as voice, dialogue, and touch. The robots emotion is generated according to a psychological theory about cognitive emotions caused by the social interaction within people. Furthermore, the emotion intensity is regulated by the loyalty level of a robot to various users. The generated emotion is dynamically expressed by facial expression, gesture, and the musical sound of the robot. The proposed system, which is composed of all the three components that are necessary for a full emotional interaction cycle, is implemented in the real robot system and tested. The proposed framework can be a cornerstone for the design of emotion interaction and generation systems for robots.