• The Journal of the Convergence on Culture Technology
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• v.7 no.4
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• pp.635-640
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• 2021

In this paper, we describe a parking space identification system that can automatically identify empty parking lot spaces from a parking lot photo. This system is based on a deep learning technique, and the accuracy of the identification result is good by learning various existing parking lot images. It could be applied to the existing parking management system. This system was also developed as a smartphone application for easy testing. Therefore, if you take a picture of a parking lot through a smartphone camera, the captured image is automatically recognized and an empty parking space can be automatically identified.

• Asia-pacific Journal of Multimedia Services Convergent with Art, Humanities, and Sociology
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• v.7 no.12
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• pp.819-829
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• 2017

In this paper, we describe the current state of speech recognition technology and identify the basic speech recognition technology and algorithms first, and then explain the code flow of API necessary for speech recognition technology. We use the application programming interface (API) of Google, Naver, and Daum KaKao, which have the most famous search engine among the speech recognition APIs, to create a voice recognition app in the Android studio tool. Then, we perform a speech recognition experiment on people's standard words and dialects according to gender, age, and region, and then organize the recognition rates into a table. Experiments were conducted on the Gyeongsang-do, Chungcheong-do, and Jeolla-do provinces where the degree of tongues was severe. And Comparative experiments were also conducted on standardized dialects. Based on the resultant sentences, the accuracy of the sentence is checked based on spacing of words, final consonant, postposition, and words and the number of each error is represented by a number. As a result, we aim to introduce the advantages of each API according to the speech recognition rate, and to establish a basic framework for the most efficient use.

• Journal of Advanced Navigation Technology
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• v.26 no.3
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• pp.172-178
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• 2022

In this paper, water meter AMR(automatic meter reading), one of the core technologies of smart water grid, using LoRa IoT network is studied. The main content of the research is to develop the network system and show the test results that one PC server receives the readings of water meters from multiple households through LoRa communication and stores them in the database, and at the same time sends the data to the web server database through internet. The system also allows users to monitor the meter readings using their smartphones. The hardware and firmware of the main board of the digital water meter are developed. For a PC server program, MDMS(meter data management system) is developed using Visual C#. The app program running on the user's smartphone is also developed using Android Studio. By connecting each developed parts, the total network system is mounted on a flow test bench in the laboratory and tested. For the fields test, 5 places around the university are selected and the transmission distances are tested. The test result show that the developed system can be applied into the real field. The developed system can be expanded to various social safety nets such as monitoring the living alone or elderly with dementia.

• Phonetics and Speech Sciences
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• v.11 no.1
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• pp.51-61
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• 2019

The purpose of this study was to develop a smartphone based voice therapy program for patients with voice disorders. Contents of voice therapy were collected through analysis of mobile contents related to voice therapy in Korea, experts and users' demand survey, and the program was developed using Android Studio. Content needed for voice therapy was collected through analysis of mobile contents related to voice therapy. The user satisfaction evaluation for application was conducted for five patient with functional voice disorders. The results showed that the mobile contents related to voice therapy in Korea were mostly related to breathing, followed by voice and singing, but only 13 applications were practically practiced for voice therapy. Expert and user demand surveys showed that the patients and therapists both had a high need for content that could provide voice training in places other than the treatment room. Based on this analysis, 'Home Voice Trainer', an smartphone based voice therapy program, was developed. Home Voice Trainer is an application for voice therapy and management based on Android smartphones. It is designed to train voice therapy activities at home that have been trained offline. In addition, the records of voice training of patients were managed online so that patients can maintain voice improvement through continuous voice consulting even after the end of voice therapy. User evaluations show that patients are satisfied with the difficulty and content of voice therapy programs provided by home voice trainers, but lack of a portion of user interface, such as the portion of home button and interface between screens. Further study suggests the clinical application of home voice trainer to the patients with voice disorders. It is expected that the development study and the clinical application of smart contents related to voice therapy will be actively conducted.