• Phonetics and Speech Sciences
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• v.12 no.2
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• pp.63-72
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• 2020

This study aims to develop a video-based smart utterance deep analyser (SUDA) application that analyzes semiautomatically the utterances that child and mother produce during interactions over time. SUDA runs on the platform of Android, iPhones, and tablet PCs, and allows video recording and uploading to server. In this device, user modes are divided into three modes: expert mode, general mode and manager mode. In the expert mode which is useful for speech and language evaluation, the subject's utterances are analyzed semi-automatically by measuring speech and language factors such as disfluency, morpheme, syllable, word, articulation rate and response time, etc. In the general mode, the outcome of utterance analysis is provided in a graph form, and the manger mode is accessed only to the administrator controlling the entire system, such as utterance analysis and video deletion. SUDA helps to reduce clinicians' and researchers' work burden by saving time for utterance analysis. It also helps parents to receive detailed information about speech and language development of their child easily. Further, this device will contribute to building a big longitudinal data enough to explore predictors of stuttering recovery and persistence.

• KIISE Transactions on Computing Practices
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• v.21 no.10
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• pp.658-669
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• 2015

The paradigm of game development changes with technological trends. If the system can analyze and determine undefined inputs, users' input choices are not restricted. Therefore, game scenarios can have multifarious flows depending upon the user's input data. In this paper, we propose a method of including an output plan in the game system that is based on the user's input but is not restricted to predefined choices. We have implemented an experimental game on the Android platform by combining network communication and APIs. The game interface works as follows: first, the user's input data is transmitted to the server using HTTP protocol; then, the server carries out an analysis on the input data; and finally, the server returns the decision result to the game device. The game can provide users a scenario that corresponds to the decision results. In this paper, we used an image file for the user's input data format. The server calculates similarities between the user's image file and reference images obtained from the Naver Image Search API and then returns determination results. We have confirmed the value of integrating the game development framework with other computing technologies demonstrating the potential of the proposed methods for application to various future game interfaces.

• Journal of the Korea Society of Computer and Information
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• v.29 no.3
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• pp.99-106
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• 2024

In this paper, we design and implement the HealthSchedule app, which records exercise data based on the GPS sensor embedded in smartphones. This app utilizes the smartphone's GPS sensor to collect real-time location information of the user and displays the movement path to the designated destination. It records the user's actual path using latitude and longitude coordinates. Users register exercise activities and destination points when scheduling, and initiate the exercise. When measuring the current location, a lime green departure marker is generated, and the movement path is displayed in blue, with the destination marker and a surrounding 25-meter radius circle shown in sky blue. Using the coordinates of the starting point or the previous location and the current GPS sensor-transmitted location coordinates, it measures the distance traveled, time taken, and calculates the speed. Furthermore, it accumulates measurement data to provide information on the total distance traveled, movement path, and overall average speed. Even when reaching the destination during exercise, the movement path continues to accumulate until the completion button is clicked. The completion button is activated when the user moves into the sky blue circular area with a radius of 25 meters, centered around the initially set destination. This means that the user must reach the designated destination, and if they wish to continue exercising without clicking the completion button, they can do so. Depending on the selected exercise type, the app displays the calories burned, aiming to increase user engagement and a sense of accomplishment.