• Journal of Institute of Control, Robotics and Systems
• /
• v.13 no.8
• /
• pp.726-734
• /
• 2007

Generally, a mobile robot is moved by original input programs. However, it is very hard for a non-expert to change the program generating the moving path of a mobile robot, because he doesn't know almost the teaching command and operating method for driving the robot. Therefore, the teaching method with speech command for a handicapped person without hands or a non-expert without an expert knowledge to generate the path is required gradually. In this study, for easily teaching the moving path of the autonomous mobile robot, the autonomous mobile robot with the function of speech recognition is developed. The use of human voice as the teaching method provides more convenient user-interface for mobile robot. To implement the teaching function, the designed robot system is composed of three separated control modules, which are speech preprocessing module, DC servo motor control module, and main control module. In this study, we design and implement a speaker dependent isolated word recognition system for creating moving path of an autonomous mobile robot in the unknown environment. The system uses word-level Hidden Markov Models(HMM) for designated command vocabularies to control a mobile robot, and it has postprocessing by neural network according to the condition based on confidence score. As the spectral analysis method, we use a filter-bank analysis model to extract of features of the voice. The proposed word recognition system is tested using 33 Korean words for control of the mobile robot navigation, and we also evaluate the performance of navigation of a mobile robot using only voice command.

• Journal of the Korean Institute of Telematics and Electronics S
• /
• v.34S no.5
• /
• pp.86-93
• /
• 1997

With recent development of speech recognition technology and multimedia computer systems, more potential applications of voice will become a reality. In this paper, we implement speech interface on the windows95 environment for practical use fo multimedia computers with voice. Speech interface is made up of three modules, that is, speech input and detection module, speech recognition module, and application module. The speech input and etection module handles th elow-level audio service of win32 API to input speech data on real time. The recognition module processes the incoming speech data, and then recognizes the spoken command. DTW pattern matching method is used for speech recognition. The application module executes the voice command properly on PC. Each module of the speech interface is designed and examined on windows95 environments. Implemented speech interface and experimental results are explained and discussed.

• Proceedings of the Korean Information Science Society Conference
• /
• 2002.04a
• /
• pp.349-351
• /
• 2002

한국현재의 컴퓨팅환경은 Text위주의 Command Line상에서의 입출력에서 GUI(Graphic User Interface)환경으로 전환되었다. 이는 사용자에게 좀더 친근한 방법으로의 컴퓨팅환경을 제공하고 있는 것이다. 하지만 아직까지 그러한 환경에 익숙해지기 위해서는 많은 습득시간이 필요하며 또한, 응용프로그램 간의 인터페이싱 기능 등을 익히기 위해서는 추가적인 학습을 통해야 원활한 작업을 수행할 수 있다. 이를 해결하고자 본 연구는 음성인식/ 합성과, 현재 음성마크업 언어인 VoiceXML 등을 통해서 모색해보고자 한다.

• Proceedings of the Korea Information Processing Society Conference
• /
• 2002.04b
• /
• pp.1495-1498
• /
• 2002

한국현재의 컴퓨팅환경은 Text위주의 Command Line상에서의 입출력에서 GUI(Graphic User Interface)환경으로 전환되었다. 이는 사용자에게 좀더 친근한 방법으로의 컴퓨팅환경을 제공하고 있는 것이다. 하지만 아직까지 그러한 환경에 익숙해지기 위해서는 많은 습득시간이 필요하며 또한 응용프로그램간의 인터페이싱 기능 등을 익히기 위해서는 추가적인 학습을 통해야 원활한 작업을 수행할 수 있다.이를 해결하고자 본 연구는 음성인식/ 합성과, 현재 음성마크업 언어인 VoiceXML 등을 통해서 모색해보고자 한다.

• Journal of the Korea Institute of Information and Communication Engineering
• /
• v.14 no.4
• /
• pp.991-998
• /
• 2010

In realization of wireless home network system using speech recognition in indoor voice recognition environment, background noise and reverberation are two main causes of digression in voice recognition system. In this study, the home network system resistant to reverberation and background noise using voice section detection method based on spectral entropy in indoor recognition environment is to be realized. Spectral subtraction can reduce the effect of reverberation and remove noise independent from voice signal by eliminating signal distorted by reverberation in spectrum. For effective spectral subtraction, the correct separation of voice section and silent section should be accompanied and for this, improvement of performance needs to be done, applying to voice section detection method based on entropy. In this study, experimental and indoor environment testing is carried out to figure out command recognition rate in indoor recognition environment. The test result shows that command recognition rate improved in static environment and reverberant room condition, using voice section detection method based on spectral entropy.

• The Journal of the Acoustical Society of Korea
• /
• v.19 no.5
• /
• pp.9-12
• /
• 2000

Voice dialing system can recognize the speaker's command and dial the destinate phone number automatically. Such a system is useful for wireless handsets and portable communication devices. As a personal voice dialing system, all the commands are used to train the HMM for speech recognition based on owner-selected phrases. Its implementation requires much less memory space and computation resource compared to a speaker-independent system. Since only two or three training utterances per command are used in this system, it is difficult to estimate exact state duration distribution to improve the recognition performance. Therefore a post-processor is presented to improve the performance. Experiments which use the database collected through the telephone line showed that the proposed post-processor improves the recognition system performance.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
• /
• 2018.10a
• /
• pp.101-102
• /
• 2018

Users who using computer may experience fatigue or sickness on their wrists if they use the keyboard and mouse for a long time. People with physical disabilities will find it difficult to work with the keyboard and mouse. There is a problem in that the substitute product for solving this is limited in function or expensive. In this paper, we development a system for controlling a personal computer with voice commands using the Amazon Echo and Amazon Web Services lambda functions. The implemented system processes the user's voice commands from the Amazon web server and sends them to the personal computer. The personal computer processes the received command and uses it to operate the application program.

• Journal of the Korean Society for Aeronautical & Space Sciences
• /
• v.41 no.12
• /
• pp.1011-1017
• /
• 2013

The human voice is the most natural means of communication. The need for speech recognition technology is increasing gradually to increase the ease of human and machine interface. The function of the avionics equipment is getting various and complicated in consequence of the growth of digital technology development, so that the load of pilots in the fighter aircraft must become increased since they don't concentrate only the attack function, but also operate the complicated avionics equipments. Accordingly, if speech recognition technology is applied to the aircraft cockpit as regards the operating the avionics equipments, pilots can spend their time and effort on the mission of fighter aircraft. In this paper, the cockpit voice command system applicable to the fighter aircraft has been developed and the function and the performance of the system verified.

• Journal of the Korean Society of Industry Convergence
• /
• v.21 no.2
• /
• pp.87-93
• /
• 2018

This Study Propose A New Approach To Impliment A Intelligent Robot Control Based on Voice Recognition For Smart Factory Automation Since human usually communicate each other by voices, it is very convenient if voice is used to command humanoid robots or the other type robot system. A lot of researches has been performed about voice recognition systems for this purpose. Hidden Markov Model is a robust statistical methodology for efficient voice recognition in noise environments. It has being tested in a wide range of applications. A prediction approach traditionally applied for the text compression and coding, Prediction by Partial Matching which is a finite-context statistical modeling technique and can predict the next characters based on the context, has shown a great potential in developing novel solutions to several language modeling problems in speech recognition. It was illustrated the reliability of voice recognition by experiments for humanoid robot with 26 joints as the purpose of application to the manufacturing process.

• Journal of Institute of Control, Robotics and Systems
• /
• v.22 no.4
• /
• pp.293-300
• /
• 2016

The Voice recognition is one of convenient methods to communicate between human and robots. This study proposes a speech recognition method using speech recognizers based on Hidden Markov Model (HMM) with a combination of techniques to enhance a biped robot control. In the past, Artificial Neural Networks (ANN) and Dynamic Time Wrapping (DTW) were used, however, currently they are less commonly applied to speech recognition systems. This Research confirms that the HMM, an accepted high-performance technique, can be successfully employed to model speech signals. High recognition accuracy can be obtained by using HMMs. Apart from speech modeling techniques, multiple feature extraction methods have been studied to find speech stresses caused by emotions and the environment to improve speech recognition rates. The procedure consisted of 2 parts: one is recognizing robot commands using multiple HMM recognizers, and the other is sending recognized commands to control a robot. In this paper, a practical voice recognition system which can recognize a lot of task commands is proposed. The proposed system consists of a general purpose microprocessor and a useful voice recognition processor which can recognize a limited number of voice patterns. By simulation and experiment, it was illustrated the reliability of voice recognition rates for application of the manufacturing process.