• Title, Summary, Keyword: Voice Recognition

Search Result 513, Processing Time 0.036 seconds

A Study on Development and Real-Time Implementation of Voice Recognition Algorithm (화자독립방식에 의한 음성인식 알고리즘 개발 및 실시간 실현에 관한 연구)

  • Jung, Yang-geun;Jo, Sang Young;Yang, Jun Seok;Park, In-Man;Han, Sung Hyun
    • Journal of the Korean Society of Industry Convergence
    • /
    • v.18 no.4
    • /
    • pp.250-258
    • /
    • 2015
  • In this research, we proposed a new approach to implement the real-time motion control of biped robot based on voice command for unmanned FA. Voice is one of convenient methods to communicate between human and robots. To command a lot of robot task by voice, voice of the same number have to be able to be recognition voice is, the higher the time of recognition is. In this paper, a practical voice recognition system which can recognition 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. Given biped robots, each robot task is, classified and organized such that the number of robot tasks under each directory is net more than the maximum recognition number of the voice recognition processor so that robot tasks under each directory can be distinguished by the voice recognition command. By simulation and experiment, it was illustrated the reliability of voice recognition rates for application of the manufacturing process.

A Study on Realization of Speech Recognition System based on VoiceXML for Railroad Reservation Service (철도예약서비스를 위한 VoiceXML 기반의 음성인식 구현에 관한 연구)

  • Kim, Beom-Seung;Kim, Soon-Hyob
    • Journal of the Korean Society for Railway
    • /
    • v.14 no.2
    • /
    • pp.130-136
    • /
    • 2011
  • This paper suggests realization method for real-time speech recognition using VoiceXML in telephony environment based on SIP for Railroad Reservation Service. In this method, voice signal incoming through PSTN or Internet is treated as dialog using VoiceXML and the transferred voice signal is processed by Speech Recognition System, and the output is returned to dialog of VoiceXML which is transferred to users. VASR system is constituted of dialog server which processes dialog, APP server for processing voice signal, and Speech Recognition System to process speech recognition. This realizes transfer method to Speech Recognition System in which voice signal is recorded using Record Tag function of VoiceXML to process voice signal in telephony environment and it is played in real time.

Voice Recognition Performance Improvement using the Convergence of Bayesian method and Selective Speech Feature (베이시안 기법과 선택적 음성특징 추출을 융합한 음성 인식 성능 향상)

  • Hwang, Jae-Chun
    • Journal of the Korea Convergence Society
    • /
    • v.7 no.6
    • /
    • pp.7-11
    • /
    • 2016
  • Voice recognition systems which use a white noise and voice recognition environment are not correct voice recognition with variable voice mixture. Therefore in this paper, we propose a method using the convergence of Bayesian technique and selecting voice for effective voice recognition. we make use of bank frequency response coefficient for selective voice extraction, Using variables observed for the combination of all the possible two observations for this purpose, and has an voice signal noise information to the speech characteristic extraction selectively is obtained by the energy ratio on the output. It provide a noise elimination and recognition rates are improved with combine voice recognition of bayesian methode. The result which we confirmed that the recognition rate of 2.3% is higher than HMM and CHMM methods in vocabulary recognition, respectively.

A Voice Command System for Autonomous Robots

  • Hong, Soon-Hyuk;Jeon, Jae-Wook
    • Transactions on Control, Automation and Systems Engineering
    • /
    • v.3 no.1
    • /
    • pp.51-57
    • /
    • 2001
  • How to promote students interest is very important in undergraduate engineering education. One of the techniques for achieving this is select appropriate projects and to integrated them with regular courses. In this paper, a voice recognition system for autonomous robots is proposed as a project to educate students about microprocessors efficiently. The proposed system consists of a microprocessor and a voice recognition processor that can recognize a limited unmber of voice patterns. The commands of autono-mous robots are classified and are organized such that one voice recognition processor can distinguish robot commands under each directory. Thus. the proposed system can distinguish more voice commands than one voice recognition processor can. A voice com-mand systems for three autonomous robots is implemented with a microprocessor Inter 80CI196KC and a voice recognition processor HM2007. The advantages in integrating this system with regular courses are also described.

  • PDF

Control System for Smart Medical Illumination Based on Voice Recognition (음성인식기반 스마트 의료조명 제어시스템)

  • Kim, Min-Kyu;Lee, Soo-In;Cho, Hyun-Kil
    • IEMEK Journal of Embedded Systems and Applications
    • /
    • v.8 no.3
    • /
    • pp.179-184
    • /
    • 2013
  • A voice recognition technology as a technology fundament plays an important role in medical devices with smart functions. This paper describes the implementation of a control system that can be utilized as a part of illumination equipment for medical applications (IEMA) based on a voice recognition. The control system can essentially be divided into five parts, the microphone, training part, recognition part, memory part, and control part. The system was implemented using the RSC-4x evaluation board which is included the micro-controller for voice recognition. To investigate the usefulness of the implemented control system, the experiments of the recognition rate was carried out according to the input distance for voice recognition. As a result, the recognition rate of the control system was more than 95% within a distance between 0.5 and 2m. The result verified that the implemented control system performs well as the smart control system based for an IEMA.

The small scale Voice Dialing System using TMS320C30 (TMS320C30을 이용한 소규모 Voice Dialing 시스템)

  • 이항섭
    • Proceedings of the Acoustical Society of Korea Conference
    • /
    • /
    • pp.58-63
    • /
    • 1991
  • This paper describes development of small scale voice dialing system using TMS320C30. Recognition vocabuliary is used 50 department name within university. In vocabulary below the middle scale, word unit recognition is more practice than phoneme unit or syllable unit recognition. In this paper, we performend recognition and model generation using DMS(Dynamic Multi-Section) and implemeted voice dialing system using TMS320C30. As a result of recognition, we achieved a 98% recognition rate in condition of section 22 and weight 0.6 and recognition time took 4 seconds.

  • PDF

Voice Recognition-Based on Adaptive MFCC and Deep Learning for Embedded Systems (임베디드 시스템에서 사용 가능한 적응형 MFCC 와 Deep Learning 기반의 음성인식)

  • Bae, Hyun Soo;Lee, Ho Jin;Lee, Suk Gyu
    • Journal of Institute of Control, Robotics and Systems
    • /
    • v.22 no.10
    • /
    • pp.797-802
    • /
    • 2016
  • This paper proposes a noble voice recognition method based on an adaptive MFCC and deep learning for embedded systems. To enhance the recognition ratio of the proposed voice recognizer, ambient noise mixed into the voice signal has to be eliminated. However, noise filtering processes, which may damage voice data, diminishes the recognition ratio. In this paper, a filter has been designed for the frequency range within a voice signal, and imposed weights are used to reduce data deterioration. In addition, a deep learning algorithm, which does not require a database in the recognition algorithm, has been adapted for embedded systems, which inherently require small amounts of memory. The experimental results suggest that the proposed deep learning algorithm and HMM voice recognizer, utilizing the proposed adaptive MFCC algorithm, perform better than conventional MFCC algorithms in its recognition ratio within a noisy environment.

Development of Language Study Machine Using Voice Recognition Technology (음성인식 기술을 이용한 대화식 언어 학습기 개발)

  • Yoo, Jae-Tack;Yoon, Tae-Seob
    • Proceedings of the KIEE Conference
    • /
    • /
    • pp.201-203
    • /
    • 2005
  • The best method to study language is to talking with a native speaker. A voice recognition technology can be used to develope a language study machine. SD(Speaker dependant) and SI(speaker independant) voice recognition method is used for the language study machine. MP3 Player. FM Radio. Alarm clock functions are added to enhance the value of the product. The machine is designed with a DSP(Digital Signal Processing) chip for voice recognition. MP3 encoder/decoder chip. FM tumer and SD flash memory card. This paper deals with the application of SD ad SD voice recognition. flash memory file system. PC download function using USB ports, English conversation text function by the use of SD flash memory. LCD display control. MP3 encoding and decoding, etc. The study contents are saved in SD flash memory. This machine can be helpful from child to adult by changing the SD flash memory.

  • PDF

A Study on Intelligent Control of Mobile Robot for Human-Robot Cooperative Operation in Manufacturing Process (인간-로봇 상호협력작업을 위한 모바일로봇의 지능제어에 관한 연구)

  • Kim, DuBeum;Bae, HoYoung;Kim, SangHyun;Im, ODeuk;Back, Young-Tae;Han, SungHyun
    • Journal of the Korean Society of Industry Convergence
    • /
    • v.22 no.2
    • /
    • pp.137-146
    • /
    • 2019
  • This study proposed a new technique to control of mobile robot based on voice command for (Human-Robot Cooperative operation in manufacturing precess). High performance voice recognition and control system was designed In this paper for smart factory. robust voice recognition is essential for a robot to communicate with people. One of the main problems with voice recognition robots is that robots inevitably effects real environment including with noises. The noise is captured with strong power by the microphones, because the noise sources are closed to the microphones. The signal-to-noise ratio of input voice becomes quite low. However, it is possible to estimate the noise by using information on the robot's own motions and postures, because a type of motion/gesture produces almost the same pattern of noise every time it is performed. In this paper, we describe an robust voice recognition system which can robustly recognize voice by adults and students in noisy environments. It is illustrated by experiments the voice recognition performance of mobile robot placed in a real noisy environment.

Voice Recognition Based on Adaptive MFCC and Neural Network (적응 MFCC와 Neural Network 기반의 음성인식법)

  • Bae, Hyun-Soo;Lee, Suk-Gyu
    • IEMEK Journal of Embedded Systems and Applications
    • /
    • v.5 no.2
    • /
    • pp.57-66
    • /
    • 2010
  • In this paper, we propose an enhanced voice recognition algorithm using adaptive MFCC(Mel Frequency Cepstral Coefficients) and neural network. Though it is very important to extract voice data from the raw data to enhance the voice recognition ratio, conventional algorithms are subject to deteriorating voice data when they eliminate noise within special frequency band. Differently from the conventional MFCC, the proposed algorithm imposed bigger weights to some specified frequency regions and unoverlapped filterbank to enhance the recognition ratio without deteriorating voice data. In simulation results, the proposed algorithm shows better performance comparing with MFCC since it is robust to variation of the environment.