• The Journal of the Acoustical Society of Korea
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• v.14 no.3
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• pp.97-104
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• 1995

This paper is a study on the recognition of continuous digits for the implementation of a voice dialing system, and proposes an method of speech recognition using syntactic analysis and One-Stage DP. In order to perform the speech recognition, first of all, we make DMS model by section division algorithm and let continuous digits data be recognized through the proposed One-Stage DP method using syntactic analysis. In this study, 7 continuous digits of 21 kinds which is pronounced by 8 male speakers two or three times, are used. The speaker dependent and speaker independent recognition are performed with the above data by way of the conventional One-Stage DP and the proposed One-Stage DP using syntactic analysis under the condition of laboratory environment. From the recognition experiments, it is shown that the proposed method was better than the established method. And, the recognition accuracy of speaker dependence and independence by the proposed One-Stage DP using syntactic analysis was about 91.7% and 89.7%.

• Proceedings of the KSR Conference
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• 2011.10a
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• pp.2775-2781
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• 2011

Urban Transit Train Radio is Radio Communication system that is used official business as leading motive for train safety running among the train crew and the central control center and drive-caring-chamber on main line and branch line. This system is operated that organizes talking path on handset of terminal after the train crew receives audio and understands call voice on speaker of terminal at calling the train of the central control center. When the central control center calls the specific train uses all call radio form, the train crew doesn't recognize the call cause the train situation, noise and action as train control. So there is a delay response cause reset call at the central control center. This research discusses the management of subway radio system and describes the call the train system that recognize train call number of all-call used between the central control center and the train crew.

• The Journal of Korea Robotics Society
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• v.4 no.3
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• pp.177-184
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• 2009

This paper presents an active assisted-living system in wireless sensor and actor network (WSAN) in which the mobile robot roles an actor. In order to provide assisted-living service to the elderly people, position recognition of the sensor node attached on the user and localization of the mobile robot should be performed at the same time. For the purpose, we use received signal strength indication (RSSI) to find the position of the person and ubiquitous sensor nodes including ultrasonic sensor which performs both transmission of sensor information and localization like global positioning system. Active services are moving to the elderly people by detecting activity sensor and visual tracking and voice chatting with remote monitoring system.

• Annual Conference of KIPS
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• 2019.10a
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• pp.1011-1013
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• 2019

4차 산업 혁명에 따라 최근 스마트홈 연구가 활발히 이루어지고 있으며 기술이 발전함에 따라 스마트홈의 개념은 변해왔다. '음성' 인터페이스를 기반으로 Google에서 제공하는 지능형 가상 비서인 Google Assistant API[1]를 이용하여 AI를 기반으로 한 음성인식 제어 수전을 제안한다. 나아가 OECD가 발표한 '심각한 물 스트레스 국가'에 속하는 대한민국 국민들에게 물 사용량의 실태를 확인하고 과다한 물 사용량에 대한 경각심을 일깨워준다.

• Journal of the Korean Institute of Intelligent Systems
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• v.11 no.6
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• pp.510-515
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• 2001

Generally, there are (1)Words for conversation (2)Tone (3)Pitch (4)Formant frequency (5)Speech speed, etc as the element for emotional recognition from speech signal. For human being, it is natural that the tone, vice quality, speed words are easier elements rather than frequency to perceive other s feeling. Therefore, the former things are important elements fro classifying feelings. And, previous methods have mainly used the former thins but using formant is good for implementing as machine. Thus. our final goal of this research is to implement an emotional recognition system based on pitch, formant, speech speed, etc. from speech signal. In this paper, as first stage we foun specific features of feeling angry from his words when a man got angry.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.18 no.5
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• pp.267-274
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• 2018

This paper introduces a smart door system composed of security system and secretary system. As ratio of single households increase, the security of household became more important. Also already there were a lot of artificial intelligence secretary system based on voice called smart home technology. But It has limits. It can not work without user's requests. That mean it is not automatic. And the voice recognition depend on user's pronounce. Thus in this paper, we design and develop smart door system that is added function of security and secretary. That can inform users that there are outsider in front of their house in real time. Also that can speak information such as user's requirements, delivery and weather information using TTS. As a result they can prevent crimes and use convenient secretary system.

• Journal of Internet Computing and Services
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• v.15 no.4
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• pp.33-42
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• 2014

Hand-signal is an effective communication means in the situation where voice cannot be used for expression especially for soldiers. Vision-based approaches using cameras as input devices are widely suggested in the literature. However, these approaches are not suitable for soldiers that have unseen visions in many cases. in addition, existing special-glove approaches utilize the information of fingers only. Thus, they are still lack for soldiers' hand-signal recognition that involves not only finger motions, but also additional information such as the rotation of a hand. In this paper, we have designed and implemented a new recognition system for six military hand-signal motions, i. e., 'ready', 'move', quick move', 'crawl', 'stop', and 'lying-down'. For this purpose, we have proposed a finger-recognition method and motion-recognition methods. The finger-recognition method discriminate how much each finger is bended, i. e., 'completely flattened', 'slightly flattened', 'slightly bended', and 'completely bended'. The motion-recognition algorithms are based on the characterization of each hand-signal motion in terms of the three axes. Through repetitive experiments, our system have shown 91.2% of correct recognition.

• Speech Sciences
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• v.15 no.1
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• pp.75-83
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• 2008

The interior of an automobile is a very noisy environment with both stationary cruising noise and the reverberated music or speech coming out from the audio system. For robust speech recognition in a car environment, it is necessary to extract a driver's voice command well by removing those background noises. Since we can handle the music and speech signals from an audio system in a car, the reverberated music and speech sounds can be removed using an acoustic echo canceller. In this paper, we implement an acoustic echo canceller with robust double-talk detection algorithm using TMS-320C6711 DSK. First we developed the echo canceller on the PC for verifying the performance of echo cancellation, then implemented it on the TMS320C6711 DSK. For processing of one speech sample with 8kHz sampling rate and 256 filter taps of the echo canceller, the implemented system used only 0.035ms and achieved the ERLE of 20.73dB.

• Journal of Digital Convergence
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• v.18 no.12
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• pp.97-103
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• 2020

The proposed system is composed of two parts, an AI physical fitness measurement part and an AI physical fitness management part. In the AI fitness measurement part, a guide to physical fitness measurement and accurate calculation of the measured value are performed through deep learning-based pose recognition. Based on these measurements, the AI fitness management part designs personalized exercise programs and provides them to dedicated smart applications. To guide the measurement posture, the posture of the subject to be measured is photographed through a webcam and the skeleton line is extracted. Next, the skeletal line of the learned preparation posture is compared with the extracted skeletal line to determine whether or not it is normal, and voice guidance is provided to maintain the normal posture.

• Journal of the Institute of Electronics Engineers of Korea TE
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• v.37 no.5
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• pp.62-70
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• 2000

In this study, speech recognition for Korean digit is performed using filter bank which is programmed discrete HMM and DTW. Spectral analysis reveals speech signal features which are mainly due to the shape of the vocal tract. And spectral feature of speech are generally obtained as the exit of filter banks, which properly integrated a spectrum at defined frequency ranges. A set of 8 band pass filters is generally used since it simulates human ear processing. And defined frequency ranges are 320-330, 450-460, 640-650, 840-850, 900-1000, 1100-1200, 2000-2100, 3900-4000Hz and then sampled at 8kHz of sampling rate. Frame width is 20ms and period is 10ms. Accordingly, we found that the recognition rate of DTW is better than HMM for Korean digit speech in the experimental result. Recognition accuracy of Korean digit speech using filter bank is 93.3% for the 24th BPF, 89.1% for the 16th BPF and 88.9% for the 8th BPF of hardware realization of voice dialing system.