• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2007.05a
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• pp.1074-1079
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• 2007

We will introduce speech/speaker recognition algorithm for the isolated word. In general case of speaker verification, Gaussian Mixture Model (GMM) is used to model the feature vectors of reference speech signals. On the other hand, Dynamic Time Warping (DTW) based template matching technique was proposed for the isolated word recognition in several years ago. We combine these two different concepts in a single method and then implement in a real time speaker/speech recognition system. Using our proposed method, it is guaranteed that a small number of reference speeches (5 or 6 times training) are enough to make reference model to satisfy 90% of recognition performance.

• Proceedings of the IEEK Conference
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• 2000.06e
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• pp.155-158
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• 2000

In this paper, For operator's conveniency of the mobile robot, achieved the system which control the robot by adopting the speaker independently isolated word recognition and by implementing the real time with TMS320C31. and This paper using the Tri-ultrasonics range finder to detect obstacles and implements the mobile robot. In this paper, DSP processor (TMS320C31) is used signal processing for speech recognition in the real time and Micro processor(80C196KC) is controling the ultrasonics range finders.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.10 no.9
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• pp.1710-1717
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• 2006

Present age the allotted span is increasing as becoming agining society gradually by scientific development and handicapped person who have native, acquired drag as long as is in mechanization of life culture is increasing. In this research to control robot through speech recognition controlling robot for handicapped person.

• 제어로봇시스템학회:학술대회논문집
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• 2000.10a
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• pp.274-274
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• 2000

In the future, the convenient speech command system will become an widely-using interface in automation systems. But the previous research in speech recognition didn't give satisfactory recognition results for the practical realization in the noise environment. The purpose of this research is the development of a practical system, which reliably recognizes the speech command of the registered users, by complementing an existing research which used the image information with the speech signal. For the lip-reading feature extraction from a image, we used the DWT(Discrete Wavelet Transform), which reduces the size and gives useful characteristics of the original image. And to enhance the robustness to the environmental changes of speakers, we acquired the speech signal by stereo method. We designed an economic stand-alone system, which adopted a Bt829 and an AD1819B with a TMS320C31 DSP based add-on board.

• Journal of the Ergonomics Society of Korea
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• v.10 no.1
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• pp.3-10
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• 1991

The teach pendant and keyboard have been used as an input device of control command in human-robot sustem. But, many problems occur in case that the usef is a novice. So, speech recognition system is required to communicate between a human and the robot. In this study, Korean voice commands, eitht robot commands, and ten digits based on the broad phonetic analysis are described. Applying broad phonetic analysis, phonemes of voice commands are divided into phoneme groups, such as plosive, fricative, affricative, nasal, and glide sound, having similar features. And then, the feature parameters and their ranges to detect phoneme groups are found by minimax method. Classification rules are consisted of combination of the feature parameters, such as zero corssing rate(ZCR), log engery(LE), up and down(UD), formant frequency, and their ranges. Voice commands were recognized by the classification rules. The recognition rate was over 90 percent in this experiment. Also, this experiment showed that the recognition rate about digits was better than that about robot commands.

• 제어로봇시스템학회:학술대회논문집
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• 2001.10a
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• pp.137.2-137
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• 2001

We have been developed an intelligent mobile robot with an artificial olfactory function to recognize odours and to track odour source location. This mobile robot also has been installed an engine for speech recognition and synthesis, and is controlled by wireless communication. An artificial olfactory system based on array of 7 gas sensors has been installed in the mobile robot for odour recognition, and 11 gas sensors also are located in the bottom of robot to track odour sources. 3 optical sensors are also included in the intelligent mobile robot, which is driven by 2 D.C. motors, for clash avoidance in a way of direction toward an odour source. Throughout the experimental trails, it is confirmed that the intelligent mobile robot is capable of not only the odour recognition using artificial neural network algorithm, but also the tracking odour source using the step-by-step approach method ...

• 제어로봇시스템학회:학술대회논문집
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• 2003.10a
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• pp.835-838
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• 2003

Computer vision and natural-language dialogue play an important role in friendly human-machine interfaces for service robots. In this paper we describe an integrated face detection and face recognition system for a welfare robot, which has also been combined with the robot's speech interface. Our approach to face detection is to combine neural network (NN) and genetic algorithm (GA): ANN serves as a face filter while GA is used to search the image efficiently. When the face is detected, embedded Hidden Markov Model (EMM) is used to determine its identity. A real-time system has been created by combining the face detection and recognition techniques. When motivated by the speaker's voice commands, it takes an image from the camera, finds the face inside the image and recognizes it. Experiments on an indoor environment with complex backgrounds showed that a recognition rate of more than 88% can be achieved.

• Transactions on Control, Automation and Systems Engineering
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• v.3 no.4
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• pp.223-228
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• 2001

We have been developed an intelligent mobile robot with an artificial olfactory function to recognize odours and to track odour source location. This mobile robot also has ben installed an engine for speech recognition and synthesis and is controlled by wireless communication. An artificial olfactory system based on array of 7 gas sensors has been installed in the mobile robot for odour recognition, and 11 gas sensors also are located in the obttom of robot to track odour sources. 3 optical sensors are also in cluded in the intelligent mobile robot, which is driven by 2 D. C. motors, for clash avoidance in a way of direction toward an odour source. Throughout the experimental trails, it is confirmed that the intelligent mobile robot is capable of not only the odour recognition using artificial neural network algorithm, but also the tracking odour source using the step-by-step approach method. The preliminary results are promising that intelligent mobile robot, which has been developed, is applicable to service robot system for environmental monitoring, localization of odour source, odour tracking of hazardous areas etc.

• Journal of the Korean Society of Industry Convergence
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• v.21 no.1
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• pp.17-27
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• 2018

We propose a new approach to control a biped robot motion based on iterative learning of voice command for the implementation of smart factory. The real-time processing of speech signal is very important for high-speed and precise automatic voice recognition technology. Recently, voice recognition is being used for intelligent robot control, artificial life, wireless communication and IoT application. In order to extract valuable information from the speech signal, make decisions on the process, and obtain results, the data needs to be manipulated and analyzed. Basic method used for extracting the features of the voice signal is to find the Mel frequency cepstral coefficients. Mel-frequency cepstral coefficients are the coefficients that collectively represent the short-term power spectrum of a sound, based on a linear cosine transform of a log power spectrum on a nonlinear mel scale of frequency. The reliability of voice command to control of the biped robot's motion is illustrated by computer simulation and experiment for biped walking robot with 24 joint.

• Proceedings of the Korean Society of Computer Information Conference
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• 2021.01a
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• pp.211-212
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• 2021

본 논문에서는 싱글보드 컴퓨터 Jetson nano 기반 음성 라이브러리 Snowboy를 활용하여 음성인식 시스템을 구현하여 Turtlebot의 동작을 제어하였다. Turtlebot은 ROS(Robot Operating System) 기반으로 동작하며 ROS core를 통해 Jetson nano와 데이터전송이 가능하다. 사용자에 의해 실시간으로 Snowboy에 저장된 특정 음성을 인식하고 지정된 좌표로 변환한다. 변환된 좌표에 따라 Turtlebot이 지정된 위치로 이동한다. Lidar센서를 활용하여 장애물을 감지하고 다른 경로를 생성해 지정된 위치로 이동한다.