• Title, Summary, Keyword: recognition

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The Study on Korean Phoneme for Korean Speech Recogintion

  • Hwang, Young-Soo
    • Proceedings of the IEEK Conference
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    • pp.629-632
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    • 2000
  • In this paper, we studied on the phoneme classification for Korean speech recognition. In the case of making large vocabulary speech recognition system, it is better to use phoneme than syllable or word as recognition unit. And, In order to study the difference of speech recognition according to the number of phoneme as recognition unit, we used the speech toolkit of OGI in U.S.A as recognition system. The result showed that the performance of diphthong being unified was better than that of seperated diphthongs, and we required the better result when we used the biphone than when using mono-phone as recognition unit.

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A Hybrid SVM-HMM Method for Handwritten Numeral Recognition

  • Kim, Eui-Chan;Kim, Sang-Woo
    • 제어로봇시스템학회:학술대회논문집
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    • pp.1032-1035
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    • 2003
  • The field of handwriting recognition has been researched for many years. A hybrid classifier has been proven to be able to increase the recognition rate compared with a single classifier. In this paper, we combine support vector machine (SVM) and hidden Markov model (HMM) for offline handwritten numeral recognition. To improve the performance, we extract features adapted for each classifier and propose the modified SVM decision structure. The experimental results show that the proposed method can achieve improved recognition rate for handwritten numeral recognition.

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

  • 이항섭
    • Proceedings of the Acoustical Society of Korea Conference
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    • pp.58-63
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    • 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.

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A Study On Text Independent Speaker Recognition Using Eigenspace (고유영역을 이용한 문자독립형 화자인식에 관한 연구)

  • 함철배;이동규;이두수
    • Proceedings of the IEEK Conference
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    • pp.671-674
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    • 1999
  • We report the new method for speaker recognition. Until now, many researchers have used HMM (Hidden Markov Model) with cepstral coefficient or neural network for speaker recognition. Here, we introduce the method of speaker recognition using eigenspace. This method can reduce the training and recognition time of speaker recognition system. In proposed method, we use the low rank model of the speech eigenspace. In experiment, we obtain good recognition result.

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Face Recognition of partial faces using LDA (LDA를 이용한 부분 얼굴 인식)

  • Park, Lee-Ju;On, Seung-Yeop
    • Proceedings of the KIEE Conference
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    • pp.1006-1009
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    • 2003
  • In this paper, we propose a technique of the recognition of partial face. Most of the research is concentrated on the recognition of whole face Since part of the face area in an image can be damaged or overlapped, face recognition based on partial face is required. PCA and LDA technique is applied to the recognition of partial face. Also, a new method to combine the results of the recognition of parts of the face.

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Pattern Recognition Methods for Emotion Recognition with speech signal

  • Park Chang-Hyun;Sim Kwee-Bo
    • International Journal of Fuzzy Logic and Intelligent Systems
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    • v.6 no.2
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    • pp.150-154
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    • 2006
  • In this paper, we apply several pattern recognition algorithms to emotion recognition system with speech signal and compare the results. Firstly, we need emotional speech databases. Also, speech features for emotion recognition are determined on the database analysis step. Secondly, recognition algorithms are applied to these speech features. The algorithms we try are artificial neural network, Bayesian learning, Principal Component Analysis, LBG algorithm. Thereafter, the performance gap of these methods is presented on the experiment result section.

Recognition Time Reduction Technique for the Time-synchronous Viterbi Beam Search (시간 동기 비터비 빔 탐색을 위한 인식 시간 감축법)

  • 이강성
    • The Journal of the Acoustical Society of Korea
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    • v.20 no.6
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    • pp.46-50
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    • 2001
  • This paper proposes a new recognition time reduction algorithm Score-Cache technique, which is applicable to the HMM-base speech recognition system. Score-Cache is a very unique technique that has no other performance degradation and still reduces a lot of search time. Other search reduction techniques have trade-offs with the recognition rate. This technique can be applied to the continuous speech recognition system as well as the isolated word speech recognition system. W9 can get high degree of recognition time reduction by only replacing the score calculating function, not changing my architecture of the system. This technique also can be used with other recognition time reduction algorithms which give more time reduction. We could get 54% of time reduction at best.

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A Real-Time Implementation of Speech Recognition System Using Oak DSP core in the Car Noise Environment (자동차 환경에서 Oak DSP 코어 기반 음성 인식 시스템 실시간 구현)

  • Woo, K.H.;Yang, T.Y.;Lee, C.;Youn, D.H.;Cha, I.H.
    • Speech Sciences
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    • v.6
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    • pp.219-233
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    • 1999
  • This paper presents a real-time implementation of a speaker independent speech recognition system based on a discrete hidden markov model(DHMM). This system is developed for a car navigation system to design on-chip VLSI system of speech recognition which is used by fixed point Oak DSP core of DSP GROUP LTD. We analyze recognition procedure with C language to implement fixed point real-time algorithms. Based on the analyses, we improve the algorithms which are possible to operate in real-time, and can verify the recognition result at the same time as speech ends, by processing all recognition routines within a frame. A car noise is the colored noise concentrated heavily on the low frequency segment under 400 Hz. For the noise robust processing, the high pass filtering and the liftering on the distance measure of feature vectors are applied to the recognition system. Recognition experiments on the twelve isolated command words were performed. The recognition rates of the baseline recognizer were 98.68% in a stopping situation and 80.7% in a running situation. Using the noise processing methods, the recognition rates were enhanced to 89.04% in a running situation.

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Google speech recognition of an English paragraph produced by college students in clear or casual speech styles (대학생들이 또렷한 음성과 대화체로 발화한 영어문단의 구글음성인식)

  • Yang, Byunggon
    • Phonetics and Speech Sciences
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    • v.9 no.4
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    • pp.43-50
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    • 2017
  • These days voice models of speech recognition software are sophisticated enough to process the natural speech of people without any previous training. However, not much research has reported on the use of speech recognition tools in the field of pronunciation education. This paper examined Google speech recognition of a short English paragraph produced by Korean college students in clear and casual speech styles in order to diagnose and resolve students' pronunciation problems. Thirty three Korean college students participated in the recording of the English paragraph. The Google soundwriter was employed to collect data on the word recognition rates of the paragraph. Results showed that the total word recognition rate was 73% with a standard deviation of 11.5%. The word recognition rate of clear speech was around 77.3% while that of casual speech amounted to 68.7%. The reasons for the low recognition rate of casual speech were attributed to both individual pronunciation errors and the software itself as shown in its fricative recognition. Various distributions of unrecognized words were observed depending on each participant and proficiency groups. From the results, the author concludes that the speech recognition software is useful to diagnose each individual or group's pronunciation problems. Further studies on progressive improvements of learners' erroneous pronunciations would be desirable.

Recognition Performance Improvement of Unsupervised Limabeam Algorithm using Post Filtering Technique

  • Nguyen, Dinh Cuong;Choi, Suk-Nam;Chung, Hyun-Yeol
    • IEMEK Journal of Embedded Systems and Applications
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    • v.8 no.4
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    • pp.185-194
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    • 2013
  • Abstract- In distant-talking environments, speech recognition performance degrades significantly due to noise and reverberation. Recent work of Michael L. Selzer shows that in microphone array speech recognition, the word error rate can be significantly reduced by adapting the beamformer weights to generate a sequence of features which maximizes the likelihood of the correct hypothesis. In this approach, called Likelihood Maximizing Beamforming algorithm (Limabeam), one of the method to implement this Limabeam is an UnSupervised Limabeam(USL) that can improve recognition performance in any situation of environment. From our investigation for this USL, we could see that because the performance of optimization depends strongly on the transcription output of the first recognition step, the output become unstable and this may lead lower performance. In order to improve recognition performance of USL, some post-filter techniques can be employed to obtain more correct transcription output of the first step. In this work, as a post-filtering technique for first recognition step of USL, we propose to add a Wiener-Filter combined with Feature Weighted Malahanobis Distance to improve recognition performance. We also suggest an alternative way to implement Limabeam algorithm for Hidden Markov Network (HM-Net) speech recognizer for efficient implementation. Speech recognition experiments performed in real distant-talking environment confirm the efficacy of Limabeam algorithm in HM-Net speech recognition system and also confirm the improved performance by the proposed method.