Pujana Paliyawan

Satoko Ito, Ruck Thawonmas, Pujana Paliyawan

This paper proposes a Minecraft-based system for early detection of Alzheimer's disease in young adults. Early detection, where spatial navigation is a crucial key, is regarded as an important way to prevent the disease. The proposed system is compared with a recent existing and thoroughly studied system using a game called Sea Hero Quest (SHQ), by analyzing spatial navigational patterns of players. Our preliminary results show that spatial navigational patterns in both systems are highly correlated, indicating that the proposed system is likely as effective as the SHQ system for the detection task.

Hong Huang, Junjie H. Xu, Xiaoling Ling et al.

To solve the existing sentence punctuation problem for collaborative commentary generation in Esports live-streaming, this paper presents two strategies for sentence punctuation for text sequences of game commentary, that is, punctuating sentences by two or three text sequence(s) originally punctuated by Youtube to obtain a complete sentence of commentary. We conducted comparative experiments utilizing and fine-tuning a state-of-the-art pre-trained generative language model among two strategies and the baseline to generate collaborative commentary. Both objective evaluations by automatic metrics and subjective analyses showed that our strategy of punctuating sentences by two text sequences outperformed the baseline.

Junjie H. Xu, Zhou Fang, Qihang Chen et al.

This paper presents a commentator for providing real-time game commentary in a fighting game. The commentary takes into account highlight cues, obtained by analyzing scenes during gameplay, as input to adjust the pitch and loudness of commentary to be spoken by using a Text-to-Speech (TTS) technology. We investigate different designs for pitch and loudness adjustment. The proposed AI consists of two parts: a dynamic adjuster for controlling pitch and loudness of the TTS and a real-time game commentary generator. We conduct a pilot study on a fighting game, and our result shows that by adjusting the loudness significantly according to the level of game highlight, the entertainment of the gameplay can be enhanced.

Junjie H. Xu, Yulin Cai, Zhou Fang et al.

This paper proposes a method for generating bullet comments for live-streaming games based on highlights (i.e., the exciting parts of video clips) extracted from the game content and evaluate the effect of mental health promotion. Game live streaming is becoming a popular theme for academic research. Compared to traditional online video sharing platforms, such as Youtube and Vimeo, video live streaming platform has the benefits of communicating with other viewers in real-time. In sports broadcasting, the commentator plays an essential role as mood maker by making matches more exciting. The enjoyment emerged while watching game live streaming also benefits the audience's mental health. However, many e-sports live streaming channels do not have a commentator for entertaining viewers. Therefore, this paper presents a design of an AI commentator that can be embedded in live streaming games. To generate bullet comments for real-time game live streaming, the system employs highlight evaluation to detect the highlights, and generate the bullet comments. An experiment is conducted and the effectiveness of generated bullet comments in a live-streaming fighting game channel is evaluated.

Zhou Fang, Pujana Paliyawan, Ruck Thawonmas et al.

This paper presents an integration of a game system and the art therapy concept for promoting the mental well-being of video game players. In the proposed game system, the player plays an Angry-Birds-like game in which levels in the game are generated based on images they draw. Upon finishing a game level, the player also receives positive feedback (praising words) toward their drawing and the generated level from an Art Therapy AI. The proposed system is composed of three major parts: (1) a drawing recognizer that identifies what object is drawn by the player (Sketcher), (2) a level generator that converts the drawing image into a pixel image, then a set of blocks representing a game level (PCG AI), and (3) the Art Therapy AI that encourages the player and improves their emotion. This paper describes an overview of the system and explains how its major components function.

Yunshi Liu, Pujana Paliyawan, Takahiro Kusano et al.

This paper proposes an image-processing-based method for personalization of calorie consumption assessment during exercising. An experiment is carried out where several actions are required in an exercise called broadcast gymnastics, especially popular in Japan and China. We use Kinect, which captures body actions by separating the body into joints and segments that contain them, to monitor body movements to test the velocity of each body joint and capture the subject's image for calculating the mass of each body joint that differs for each subject. By a kinetic energy formula, we obtain the kinetic energy of each body joint, and calories consumed during exercise are calculated in this process. We evaluate the performance of our method by benchmarking it to Fitbit, a smart watch well-known for health monitoring during exercise. The experimental results in this paper show that our method outperforms a state-of-the-art calorie assessment method, which we base on and improve, in terms of the error rate from Fitbit's ground-truth values.

Pujana Paliyawan, Takahiro Kusano, Yuto Nakagawa et al.

This paper presents a design of a non-player character (AI) for promoting balancedness in use of body segments when engaging in full-body motion gaming. In our experiment, we settle a battle between the proposed AI and a player by using FightingICE, a fighting game platform for AI development. A middleware called UKI is used to allow the player to control the game by using body motion instead of the keyboard and mouse. During gameplay, the proposed AI analyze health states of the player; it determines its next action by predicting how each candidate action, recommended by a Monte-Carlo tree search algorithm, will induce the player to move, and how the player's health tends to be affected. Our result demonstrates successful improvement in balancedness in use of body segments on 4 out of 5 subjects.