• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2021.10a
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• pp.320-322
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• 2021

As the world's elderly population increases, the proportion of visually impaired is also increasing, and there are still many restrictions on the use of outside activities, such as safety problems and lack of guidance information. To solve this problem, research on smart devices such as smart glasses with optical character recognition (OCR) function is being actively conducted. In this paper, we propose a system that recognizes obstacles ahead and informs information by voice, and also guides the way to the destination. Using the deep learning object recognition model Yolo, it let them to recognize the risk factors as obstacles such as stairs and Larva cones. and it also deliver the information with a voice. so you can expect that the visually impaired can do a lot of different activity even more now that system takes the visually impaired to the destination by using the directions API, voice recognition, TTS library.

• Proceedings of the Korean Society of Computer Information Conference
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• 2015.07a
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• pp.339-340
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• 2015

시각장애인은 주변 인지 장애로 정보 습득이 어렵고, 공간 정보 습득에 있어서 제약이 있는 신체조건으로 이동에 불편을 겪는다. 또한 특정 상황에서 적절한 분위기를 인지하고 그에 맞는 대응을 하기가 어렵다. IoT 시대에 맞춰 홈 네트워크 시스템이 널리 보급되어지는 추세이지만, 여전히 시각장애인이 사용하기에는 많은 어려움이 있고, 불편을 호소하는 게 현실이다. 본 논문에서는 이러한 시각장애인을 위해 스마트폰을 이용해 음성으로 집안의 사물을 원격 제어하는 구글 음성인식 홈 리모트 컨트롤 시스템을 제안한다.

• Proceedings of the Korean Society of Computer Information Conference
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• 2012.07a
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• pp.269-270
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• 2012

본 논문에서는 키패드로만 동작하는 디지털 도어락에 보안을 강화하기 위해 음성 인식 장치를 추가한 음성 인식 디지털 도어락을 설계하고 구현하였다. 비밀번호로만 동작하는 도어락은 비밀번호의 분실 가능성이 있기 때문에 보안을 위해서는 화자의 특징을 인식할 수 있는 화자 종속 방식의 음성인식이 효율적이다. 본 논문에서 제안하는 방식은 가정집뿐만이 아니라 회사에서 보다 높은 수준의 보안이 필요한 곳에서 사용이 가능하다. 또한 구현한 시스템은 장애인을 위해 음성만으로 동작하는 시스템 등으로 쉽게 변경이 가능하다. 제안한 시스템은 ATmega128을 기반으로 키패드, 텍스트 LCD, 음성인식 모듈을 결합하여 구성하였다.

• MALSORI
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• no.52
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• pp.161-169
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• 2004

This paper describes the automated call routing for train ticket reservation aid system based on speech recognition. We focus on the task of automatically routing telephone calls based on user's fluently spoken response instead of touch tone menus in an interactive voice response system. Vector-based call routing algorithm is investigated and mapping table for key term is suggested. Korail database collected by KT is used for call routing experiment. We evaluate call-classification experiments for transcribed text from Korail database. In case of small training data, an average call routing error reduction rate of 14% is observed when mapping table is used.

• Proceedings of the IEEK Conference
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• 2002.07a
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• pp.690-693
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• 2002

According to the growth of communication biz, embedded market rapidly developing in domestic and overseas. Embedded system can be used in various way such as wire and wireless communication equipment or information products. There are lots of developing performance applying speech recognition to embedded system, for instance, PDA, PCS, CDMA-2000 or IMT-2000. This study implement minimum memory of speech recognition engine and DB for apply real time embedded system. The implement measure of speech recognition equipment to fit on embedded system is like following. At first, DC element is removed from Input voice and then a compensation of high frequency was achieved by pre-emphasis with coefficients value, 0.97 and constitute division data as same size as 256 sample by lapped shift method. Through by Levinson - Durbin Algorithm, these data can get linear predictive coefficient and again, using Cepstrum - Transformer attain feature vectors. During HMM training, We used Baum-Welch reestimation Algorithm for each words training and can get the recognition result from executed likelihood method on each words. The used speech data is using 40 speech command data and 10 digits extracted form each 15 of male and female speaker spoken menu control command of Embedded system. Since, in many times, ARM CPU is adopted in embedded system, it's peformed porting the speech recognition engine on ARM core evaluation board. And do the recognition test with select set 1 and set 3 parameter that has good recognition rate on commander and no digit after the several tests using by 5 proposal recognition parameter sets. The recognition engine of recognition rate shows 95%, speech commander recognizer shows 96% and digits recognizer shows 94%.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.17 no.5
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• pp.17-23
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• 2017

A connected car's major factor is connectivity and it can be applied for new concept smart PC hardware and software design method of digital virtual assistance using voice recognition engine at server when infotainment functions are implemented because internet connecting LTE or 5G wireless mobile communication is always is possible. In this paper, a hardware architecture of smart auto-PC and software architecture based on GENIVI platform, and necessary functions are proposed. Also an effective analysis and design method of connected car infotainment system will be presented by showing user requirement analysis using object-oriented method, flowchart and screen design.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.19 no.1
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• pp.179-185
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• 2019

A core technology of social robot is voice recognition and dialogue engine technology, but too much money is needed for development and an implementation of robot's conversation function is difficult resulting from insufficiency of performance. Dialogue function's implementation between human and robot can be possible due to advance of cloud AI technology and several company's supply of their open API. In this paper, current intelligent social robot technology trend is investigated and effective social robot system architecture is designed. Also an effective analysis and design method of social robot system will be presented by showing user requirement analysis using object-oriented method, flowchart and screen design.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 2003.09a
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• pp.315-317
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• 2003

Neural oscillator is applied in oscillatory systems (Analysis of image information, Voice recognition. Etc...). If we apply established EBPA(Error back Propagation Algorithm) to oscillatory system, we are difficult to presume complicated input's patterns. Therefore, it requires more data at training, and approximation of convergent speed is difficult. In this paper, I studied the neural oscillator as synchronized states with appropriate phase relation between neurons and recognized the Korean alphabet using Neural Oscillator Phase model Synchronization.

• Journal of Korea Multimedia Society
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• v.16 no.3
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• pp.302-308
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• 2013

In this research, we have explored personal authentication system through multimodal biometrics for mobile computing environment. We have selected face and speaker recognition for the implementation of multimodal biometrics system. For face recognition part, we detect the face with Modified Census Transform (MCT). Detected face is pre-processed through eye detection module based on k-means algorithm. Then we recognize the face with Principal Component Analysis (PCA) algorithm. For speaker recognition part, we extract features using the end-point of voice and the Mel Frequency Cepstral Coefficient (MFCC). Then we verify the speaker through Dynamic Time Warping (DTW) algorithm. Our proposed multimodal biometrics system shows improved verification rate through combining two different biometrics described above. We implement our proposed system based on Android environment using Galaxy S hoppin. Proposed system presents reduced false acceptance ratio (FAR) of 1.8% which shows improvement from single biometrics system using the face and the voice (presents 4.6% and 6.7% respectively).

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 1998.11a
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• pp.181-185
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• 1998

Recently, research and developmental direction of communication system is concurrent adopting voice data and face image in speaking to provide more higher recognition rate then in the case of only voice data. Therefore, we present a method of lipreading in speech image sequence by using the 3-D facial shape model. The method use a feature information of the face image such as the opening-level of lip, the movement of jaw, and the projection height of lip. At first, we adjust the 3-D face model to speeching face image sequence. Then, to get a feature information we compute variance quantity from adjusted 3-D shape model of image sequence and use the variance quality of the adjusted 3-D model as recognition parameters. We use the intensity inclination values which obtaining from the variance in 3-D feature points as the separation of recognition units from the sequential image. After then, we use discrete HMM algorithm at recognition process, depending on multiple observation sequence which considers the variance of 3-D feature point fully. As a result of recognition experiment with the 8 Korean vowels and 2 Korean consonants, we have about 80% of recognition rate for the plosives and vowels.