• IEMEK Journal of Embedded Systems and Applications
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• v.2 no.1
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• pp.43-52
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• 2007

IEEE 802.15.4 specification which defines low-rate wireless personal area network(LR-WPAN) has application to home or building automation, remote control and sensing, intelligent management, environmental monitoring, and so on. Recently, it has been considered as an alternative technology to provide multimedia services such as automation via voice recognition, wireless headset and wireless camera for surveillance. In order to evaluate capability of voice traffic on the IEEE 802.15.4 LR-WPAN, we supposed two scenarios, voice traffic only and coexistence of voice and sensing traffic. For both cases we examined delay and packet loss rate in case of with and without acknowledgement, and various beacon period varying with beacon and superframe order values. In LR-WPAN with voice devices only, total 5 voice devices could be applicable and in the other case, i.e., coexisted cases of voice and sensor devices, a voice device was able to coexist with about 60 sensor devices.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.38C no.3
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• pp.239-246
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• 2013

The IEEE 802.15.4 offers standard about PHY and MAC layer and features low power, low bandwidth, and low speed data communication. Because of this reason, IEEE 802.15.4 is only within a limited range such as sensor detection and home network; nevertheless, the research about transmission multimedia data like voice packet through wireless sensor networks is conducted widely. In this paper, we proposed the group communication system based on the sensor network. TDMA/TDD MAC based on the IEEE 802.15.4 PHY for voice communication on the sensor network is designed by improvement existing peer-to-peer voice communication on the sensor network and hardware is implemented for group communication. To measure the quality of designed system, mean opinion score (MOS) is obtained from the experiment and verified by using sine wave method. As a result of an experiment, we expect that a many cases of application solution can be developed using presented system.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.37B no.11
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• pp.1004-1013
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• 2012

The legacy voice broadcast systems are used to broadcast the voice over an entire space or a specific zone. these broadcast systems generate unnecessary noise and waste of resources. In this paper, we propose a ubiquitous voice message broadcast system called uPaging, by combining the technique of location-awareness and the voice message delivery service in ubiquitous sensor network environment. In uPaging system, the wire/wireless hybrid network is used to implement the network system. Also, in order to actualize the location-awareness service, we use the Bidirectional Location ID-Exchange protocol was suggested by our previous research. the uPaging system can deliver the voice to a selected user or the location in which the user is present by this location awareness.

• Speech Sciences
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• v.11 no.1
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• pp.21-29
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• 2004

In this paper we examined the effect of normalization on discriminating the pathological voice into normal and abnormal classes using artificial neural network. Average values per each parameter were used to normalize each set of parameter values. Artificial neural networks were used as classifiers. And the effect of normalization was evaluated by comparing the discrimination results between original and normalized parameter sets.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.19 no.7
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• pp.1346-1363
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• 1994

Packet voice protocols have been realized in many research works. But few studies for the interconnection of LAN and PABX to facilitate the voice communication have been done. In this paper, the gateway to interconnect the Ethernet LAN with the existing PABX telephone network for voice communication has been designed and implemented. The implemented gateway protocol is a modified protocol based on CCITT`s G.764 packetized voice protocol. To accomplish this goal the hardware system has been realized, which is divided into five parts: interface part with the telephone line, voice-processing part, PC interface part, controller part, and finally DTMF part. And the gateway software is divided into three parts: interface to make use of the packet driver which drives the network card, driver to drive the PABX gateway, and the protocol handling part.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.21 no.2
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• pp.55-60
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• 2021

As the smart factory progresses, the use of automation facilities and robots is increasing. Also, with the development of IT technology, the utilization of the system using voice recognition is also increasing. Voice recognition technology is a technology that stands out in smart home and various IoT technologies, but it is difficult to apply to factories due to the specificity of factories. Therefore, in this study, a method to control an industrial articulated robot was designed using voice recognition technology that considers the situation at the manufacturing site. It was confirmed that the robot could be controlled through network protocol and command conversion after receiving voice commands for robot operation through mobile.

• Journal of Korea Multimedia Society
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• v.13 no.4
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• pp.594-600
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• 2010

Many studies are DDoS in Internet network, but the study is the fact that is not enough in a voice network. Therefore, we designed the extended TRW algorithm that was a DDoS attack traffic detection algorithm for the voice network which used an IP data network to solve upper problems in this article and evaluated it. The algorithm that is proposed in this paper analyzes TRW algorithm to detect existing DDoS attack in Internet network and, design connection and end connection to apply to a voice network, define probability function to count this. For inspect the algorithm, Set a threshold and using NS-2 Simulator. We measured detection rate by an attack traffic type and detection time by attack speed. At the result of evaluation 4.3 seconds for detection when transmitted INVITE attack packets per 0.1 seconds and 89.6% performance because detected 13,453 packet with attack at 15,000 time when transmitted attack packet.

• The Journal of Korean Institute of Information Technology
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• v.16 no.11
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• pp.11-21
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• 2018

Research is carried out to categorize voices using Deep Learning technology. The study examines neural network-based sound classification studies and suggests improved neural networks for voice classification. Related studies studied urban data classification. However, related studies showed poor performance in shallow neural network. Therefore, in this paper the first preprocess voice data and extract feature value. Next, Categorize the voice by entering the feature value into previous sound classification network and proposed neural network. Finally, compare and evaluate classification performance of the two neural networks. The neural network of this paper is organized deeper and wider so that learning is better done. Performance results showed that 84.8 percent of related studies neural networks and 91.4 percent of the proposed neural networks. The proposed neural network was about 6 percent high.

• Speech Sciences
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• v.15 no.2
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• pp.89-97
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• 2008

There is a number of clinical conditions that affect directly or indirectly the physical properties of the vocal folds and thereby the pressure waveforms of elicited sounds. If the relationships between the clinical conditions and the voice quality are sufficiently reliable, it should be possible to detect these diseases or disorders. The focus of this paper is to determine the set of features and their values that would characterize the speaker's state of vocal folds. To the extent that these features can capture the anatomical, physiological, and neurological aspects of the speaker they can be potentially used to mediate an unobtrusive approach to diagnosis. We will show a new approach to this problem supported with results obtained from two disordered voice corpora.

• International Journal of Computer Science & Network Security
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• v.24 no.1
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• pp.205-208
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• 2024

Artificial Intelligence (AI) technology has evolved rapidly in recent years and is used in everything from banking to email management to surgery, but without the help of the visible, most of the fun features of the Internet include visual impairment. It benefits people with disabilities. The main purpose of this study is to find ways to help people with visual impairments using AI technology. A visually impaired request is made for the visually impaired. For example, when a message arrives that the program will notify you by voice (reads the sender's name, read the message, and replies to it if necessary), this is a special program installed on your mobile phone. This program uses a customized algorithm developed in Python to convert written text to voice, read text, and convert voice to written text on a message when a visually impaired person wants to respond. Then it sends the response in the form of a text message. Therefore, the research should lead to programs for people with visual impairments. This program makes mobile phones easier and more comfortable to use and makes the daily life easier for visual impairments.