• ETRI Journal
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• v.28 no.2
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• pp.250-252
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• 2006

In this letter, a discrete state, discrete time chaotic pseudo random number generator (CPRNG) is presented for stream ciphering of text, audio, or image data. The CPRNG is treated as a finite state machine, and its state is modulated according to the input bit sequence of the signal to be encrypted. The modulated state sequence obtained can be transmitted as a spread spectrum or encrypted data.

• The Journal of the Acoustical Society of Korea
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• v.8 no.4
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• pp.65-73
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• 1989

In this paper, we propose a text-independent speaker identification algorithm based on VQ(vector quantization) and vowel classification, and its performance is studied and compared with that of a conventional speaker identification algorithm using VQ. The proposed speaker identification algorithm is composed of three processes: vowel segmentation, vowel recognition and average distortion calculation. The vowel segmentation is performed automatlcally using RMS energy, BTR(Back-to-Total cavity volume Ratio)and SFBR(Signed Front-to-Back maximum area Ratio) extracted from input speech signal. If the Input speech signal Is noisy, particularity when the SNR is around 20dB, the proposed speaker identification algorithm performs better than the reference speaker identification algorithm when the correct vowel segmentation is done. The same result is obtained when we use the noisy telephone speech signal as an input, too.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.8 no.7
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• pp.1546-1552
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• 2004

Electronic Ink is a stored data in the form of the handwritten text or the script without converting it into ASCII by handwritten recognition on the pen-based computers and Personal Digital Assistants(Pocket PC) for supporting natural and convenient data input. One of the most important issues is to search the electronic ink in order to use it. We proposed and implemented a script matching algorithm for the electronic ink. Proposed matching algorithm separated the input stroke into a set of primitive stroke using the curvature of the stroke curve. After determining the type of separated strokes, it produced a stroke feature vector. And then it calculated the distance between the stroke feature vector of input strokes and one of strokes in the database using the dynamic programming technique.

• Journal of Korea Society of Digital Industry and Information Management
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• v.20 no.2
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• pp.27-36
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• 2024

Accidents or disease can lead to acquired voice dysphonia. In this case, we propose a new input interface based on eye movements to facilitate communication for patients. Unlike the existing method that presents the English alphabet as it is, we reorganized the layout of the alphabet to support the Korean alphabet and designed it so that patients can enter words by themselves using only eye movements, gaze, and blinking. The proposed interface not only reduces fatigue by minimizing eye movements, but also allows for easy and quick input through an intuitive arrangement. For natural communication, we also implemented a system that allows patients who are unable to speak to communicate with their own voice. The system works by tracking eye movements to record what the patient is trying to say, then using Glow-TTS and Multi-band MelGAN to reconstruct their own voice using the learned voice to output sound.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.42 no.2
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• pp.349-357
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• 2017

Many Web sites adopt SMS(Short Message Service)-based user authentication when a user loses her password or approves an online payment. In SMS-based authentication, the authentication server sends a text in plaintext to a user's phone, and it allows an attacker who eavesdrops or intercepts the text to impersonate a valid user(victim). We propose a challenge-response scheme to prove to the authentication server that a user is in a certain place at the moment with her smartphone beside her. The proposed scheme generates a response using a challenge by the server, user's current location, and a secret on the user's smartphone all together. Consequently, the scheme is much more secure than SMS-based authentication that simply asks a user to send the same text arrived on her phone back to the server. In addition to entering the response, which substitutes the SMS text, the scheme also requests a user to input a passphrase to get the authentication process started. We believe, however, the additional typing should be tolerable to most users considering the enhanced security level of the scheme.

• Journal of KIISE:Software and Applications
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• v.34 no.6
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• pp.572-583
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• 2007

This paper investigates Centering-based metrics to evaluate ordering of utterances for text structuring. We point out a problem of MIN.NOCB metric which has been regarded as the simplest and best measure to evaluate coherence of ordering within Centering framework, and propose a new Centering-based metric, MAX.CPS as an alternative or supplementary one. This paper introduces a framework which pre-estimates the effectiveness of a metric on a given input ordering, and selects an applicable metric according to the pre-estimation result. Using this framework, we propose a new policy which can generate more optimal ordering within Centering framework. Moreover, we evaluate several kinds of Cf-ranking methods in terms of Centering-based metrics, and find that simply ranking entities by their linear order is generally the most suitable because of characteristics in Korean.

• Journal of Intelligence and Information Systems
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• v.24 no.4
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• pp.85-110
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• 2018

A chatbot is an interactive assistant that utilizes many communication modes: voice, images, video, or text. It is an artificial intelligence-based application that responds to users' needs or solves problems during user-friendly conversation. However, the current version of the chatbot is focused on understanding and performing tasks requested by the user; its ability to generate personalized conversation suitable for relationship-building is limited. Recognizing the need to build a relationship and making suitable conversation is more important for social chatbots who require social skills similar to those of problem-solving chatbots like the intelligent personal assistant. The purpose of this study is to propose a text analysis method that evaluates relationships between chatbots and users based on content input by the user and adapted to the communication situation, enabling the chatbot to conduct suitable conversations. To evaluate the performance of this method, we examined learning and verified the results using actual SNS conversation records. The results of the analysis will aid in implementation of the social chatbot, as this method yields excellent results even when the private profile information of the user is excluded for privacy reasons.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.17 no.8
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• pp.2278-2291
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• 2023

Imported ornamental fish should be quarantined because they can have dangerous diseases depending on their habitat. The quarantine requires a lot of time because quarantine officers collect various information on the imported ornamental fish. Inefficient quarantine processes reduce its work efficiency and accuracy. Also, long-time quarantine causes the death of environmentally sensitive ornamental fish and huge financial losses. To improve existing quarantine systems, information on ornamental fish was collected and structured, and a server was established to develop quarantine performance support software equipped with a text search engine. However, the long names of ornamental fish in general can cause many typos and time bottlenecks when we type search words for the target fish information. Therefore, we need a technique that can correct typos. Typical typo character calibration compares input text with all characters in a calibrated candidate text dictionary. However, this approach requires computational power proportional to the number of typos, resulting in slow processing time and low calibration accuracy performance. Therefore, to improve the calibration accuracy of characters, we propose a fusion system of simple Artificial Neural Network (ANN) models and character preprocessing methods that accelerate the process by minimizing the computation of the models. We also propose a typo character generation method used for training the ANN models. Simulation results show that the proposed typo character correction system is about 6 times faster than the conventional method and has 10% higher accuracy.

• The Korean Journal of Applied Statistics
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• v.36 no.6
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• pp.501-514
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• 2023

When analyzing high dimensional data such as text data, if we input all the variables as explanatory variables, statistical learning procedures may suffer from over-fitting problems. Furthermore, computational efficiency can deteriorate with a large number of variables. Dimensionality reduction techniques such as feature selection or feature extraction are useful for dealing with these problems. The sparse principal component analysis (SPCA) is one of the regularized least squares methods which employs an elastic net-type objective function. The SPCA can be used to remove insignificant principal components and identify important variables from noisy observations. In this study, we propose a dimension reduction procedure for text data based on the SPCA. Applying the proposed procedure to real data, we find that the reduced feature set maintains sufficient information in text data while the size of the feature set is reduced by removing redundant variables. As a result, the proposed procedure can improve classification accuracy and computational efficiency, especially for some classifiers such as the k-nearest neighbors algorithm.

• Journal of the Korea Society of Computer and Information
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• v.29 no.4
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• pp.23-30
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• 2024

In this paper, we propose a deep learning-based personalized senior care service application. The proposed application uses Speech to Text technology to convert the user's speech into text and uses it as input to Autogen, an interactive multi-agent large-scale language model developed by Microsoft, for user convenience. Autogen uses data from previous conversations between the senior and ChatBot to understand the other user's intent and respond to the response, and then uses a back-end agent to create a wish list, a shared calendar, and a greeting message with the other user's voice through a deep learning model for voice cloning. Additionally, the application can perform home IoT services with SKT's AI speaker (NUGU). The proposed application is expected to contribute to future AI-based senior care technology.