• Journal of the Semiconductor & Display Technology
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• v.23 no.3
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• pp.140-147
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• 2024

This paper explores the recent advancements in speech recognition technology, focusing on the integration of artificial intelligence to improve recognition accuracy in challenging environments, such as noisy or low-quality audio conditions. Traditional speech recognition methods often suffer from performance degradation in noisy settings. However, the application of deep neural networks (DNN) has led to significant improvements, enabling more robust and reliable recognition in various industries, including banking, automotive, healthcare, and manufacturing. A key area of advancement is the use of Silent Speech Interfaces (SSI), which allow communication through non-speech signals, such as visual cues or other auxiliary signals like ultrasound and electromyography, making them particularly useful for individuals with speech impairments. The paper further discusses the development of multi-modal speech recognition, combining both audio and visual inputs, which enhances recognition accuracy in noisy environments. Recent research into lip-reading technology and the use of deep learning architectures, such as CNN and RNN, has significantly improved speech recognition by extracting meaningful features from video signals, even in difficult lighting conditions. Additionally, the paper covers the use of self-supervised learning techniques, like AV-HuBERT, which leverage large-scale, unlabeled audiovisual datasets to improve performance. The future of speech recognition technology is likely to see further integration of AI-driven methods, making it more applicable across diverse industries and for individuals with communication challenges. The conclusion emphasizes the need for further research, especially in languages with complex morphological structures, such as Korean

• Journal of the Semiconductor & Display Technology
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• v.19 no.2
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• pp.100-104
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• 2020

Over the past several years, deep learning has been widely used for feature extraction in image and video for various applications such as object classification and facial recognition. This paper introduces an implantation of embedded Linux system for embossed digits recognition using CNN based deep learning methods. For this purpose, we implemented a coin recognition system based on deep learning with the Keras open source library on Raspberry PI. The performance evaluation has been made with the success rate of coin classification using the images captured with ultra-wide angle camera on Raspberry PI. The simulation result shows 98% of the success rate on average.

• Journal of the Semiconductor & Display Technology
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• v.19 no.2
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• pp.60-67
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• 2020

Recently, artificial intelligence related technologies including machine learning are being applied to various fields, and the demand is also increasing. In particular, with the development of AR, VR, and MR technologies related to image processing, the utilization of computer vision based on deep learning has increased. The algorithms for object recognition and detection based on deep learning required for image processing are diversified and advanced. Accordingly, problems that were difficult to solve with the existing methodology were solved more simply and easily by using deep learning. This paper introduces various deep learning-based object recognition and extraction algorithms used to detect and recognize various objects in an image and analyzes the technologies that attract attention.

• Electronics and Telecommunications Trends
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• v.33 no.6
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• pp.24-33
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• 2018

In the age of IoT, in which everything is connected to a network, there have been increases in the amount of data traffic, latency, and the risk of personal privacy breaches that conventional cloud computing technology cannot cope with. The idea of edge computing has emerged as a solution to these issues, and furthermore, the concept of ultra-low power edge intelligent semiconductors in which the IoT device itself performs intelligent decisions and processes data has been established. The key elements of this function are an intelligent semiconductor based on artificial intelligence, connectivity for the efficient connection of neurons and synapses, and a large-scale spiking neural network simulation framework for the performance prediction of a neural network. This paper covers the current trends in ultra-low power edge intelligent semiconductors including issues regarding their technology and application.

• Journal of the Semiconductor & Display Technology
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• v.20 no.1
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• pp.83-87
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• 2021

By the increase of internet usage, communicating online became an everyday thing. Thereby various people have experienced profanity by anonymous users. Nowadays lots of studies tried to solve this problem using artificial intelligence, but most of the solutions were for non-real time situations. In this paper, we propose a Telegram plugin that detects swear words using word2vec, and an algorithm to find the target of the sentence. We vectorized the input sentence to find connections with other similar words, then inputted the value to the pre-trained CNN (Convolutional Neural Network) model to detect any swears. For target recognition we proposed a sequential algorithm based on KoNLPY.

• Journal of the Semiconductor & Display Technology
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• v.20 no.2
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• pp.115-120
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• 2021

In Korea, where the world's first cloud computing development law was created, cloud service technology has been developing so far, and the industries to which artificial intelligence and big data technologies can be applied based on this are increasing. It is important for domestic and overseas cloud operators to secure many partners in order to provide optimal services to users. It is also important to systematically develop the partner's technology and discover new partners. In particular, the public, medical, and financial sectors are industrial fields that are difficult for domestic as well as global cloud service providers to expand without the help of partners. This study analyzes partner policies for industries caused by domestic regulations through domestic and foreign cases, and aims to establish partner management policies optimized for the domestic environment.

• Journal of the Semiconductor & Display Technology
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• v.21 no.3
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• pp.110-113
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• 2022

Non-playable game character plays an important role in improving the concentration of the game and the interest of the user, and recently implementation of NPC with reinforcement learning has been in the spotlight. In this paper, we estimate an AI target tracking method via reinforcement learning, and implement an AI-based tracking agency of specific target object with avoiding traps through Unity ML-Agents Toolkit. The implementation is built in Unity game engine, and simulations are conducted through a number of experiments. The experimental results show that outstanding performance of the tracking target with avoiding traps is shown with good enough results.

• Journal of the Semiconductor & Display Technology
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• v.20 no.4
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• pp.83-88
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• 2021

Cloud services have become the core infrastructure of the digital economy as a basis for collecting, storing, and processing large amounts of data to trigger artificial intelligence-based services and industrial innovation. Recently, cloud services have been spotlighted as a means of responding to corporate crises and changes in the work environment in a national disaster caused by COVID-19. While the cloud is attracting attention, the speed of adoption and diffusion of cloud services is not being actively carried out due to the lack of trust among users and uncertainty about security, performance, and cost. This study compares and analyzes the "Cloud Service Quality and Performance Management System" and the "Cloud Service Certification System" and suggests complementary points and improvement measures for the cloud service quality and performance management system.

• Journal of the Semiconductor & Display Technology
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• v.21 no.1
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• pp.1-4
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• 2022

As computers can express and utilize information in a semantic dimension different from the real world, humans have opened the door to the digital world and have played a pivotal role in the transformation of the human habitual environment. Using metaverse, it can be possible to predict concepts such as virtual currency, artificial intelligence, and virtual reality, which have now become possible for practical systemic visualization. In order to implement the metaverse in the realm of technology, it requires not only a multifaceted discussion on the platform, but also research on an architect that can include the intrinsic complexity of the metaverse. In this paper, we discuss the architecture for an open metaverse platform based on convergence wrapping that can converge various contents into one space, and propose a comprehensive platform design.

• Journal of the Semiconductor & Display Technology
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• v.22 no.4
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• pp.76-80
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• 2023

This study is about a service that allows people to naturally learn to bask in the sun, which is a habit to relieve depression. Modern people do not have enough time to bask in the sun due to their busy lives, and as a result, depression and fatigue are increasing day by day. Therefore, in order to relieve depression, there is a need for the development of technology to manage the schedule of sunlight basking so that users can experience sunlight more naturally. The sunlight service developed through this study can help you easily plan your sunlight schedule by recommending good dates, times, and locations for sunbathing. In addition, users can receive coins as much as they bask in the sun, and they can be motivated by the act of basking in the sun by raising their character with those coins.