• Title/Summary/Keyword: Cepstrum

Search Result 274, Processing Time 0.024 seconds

An Improved Digit Recognition using Normalized mel-cepstrum (정규화된 Mel-cepstrum을 이용한 숫자음 인식성능 향상에 관한 연구)

  • 이기철
    • Proceedings of the Acoustical Society of Korea Conference
    • /
    • 1994.06c
    • /
    • pp.403-406
    • /
    • 1994
  • 음성은 화자의 상태 및 주변 환경에 따라 그 특징이 다양하게 변화한다. 본 논문에서는 음성신호의 특징 파라미터로 널리 쓰이고 있는 mel-cepstrum에 대해, 단어내에서의 변화를 정규화함으로써 인식성능을 향상시키고자 하였다. mel-cepstrum이란 단어 전체에 대한 mel-cepstrum의 평균 값으로 normalize 시킨 것이다. 한국어 숫자음에 대한 인식 실험결과, 본 논문에서 제안한 정규화된 mel-cepstrum이 정규화되지 않은 mel-cepstrum에 비해 우수한 인식 성능을 나타내었다. 또한 잡음 환경하에서 비교 실험한 결과에서도 상대적으로 우수한 인식률을 보였다.

  • PDF

Detection of Impulse Signal in Noise Using a Minimum Variance Cepstrum-Theory (최소 분산 캡스트럼을 이용한 노이즈속에 묻힌 임펄스 검출방법-이론)

  • 최영철;김양한
    • Journal of KSNVE
    • /
    • v.10 no.4
    • /
    • pp.642-647
    • /
    • 2000
  • Conventional cepstrum has been widely used to detect echo and fault signals embedded in noise. One of the problems of finding impulse signals using the conventional cepstrum in that it is normally very sensitive to signal to noise ratio (SNR). This paper proposes a signal processing method to detect impulse signal in noisy environment. Because the proposed method minimizes the variance of signal power at a cepstrum domain, it is suggested to be called as minimum variance cepstrum (MV cepstrum). Computer simulations have been performed to understand the characteristics of the MV cepstrum. Both mathematical approach and computer simulations confirmed that the MV cepstrum is a useful technique to detect impulse in noisy environment.

  • PDF

Glottal Weighted Cepstrum for Robust Speech Recognition (잡음에 강한 음성 인식을 위한 성문 가중 켑스트럼에 관한 연구)

  • 전선도;강철호
    • The Journal of the Acoustical Society of Korea
    • /
    • v.18 no.5
    • /
    • pp.78-82
    • /
    • 1999
  • This paper is a study on weighted cepstrum used broadly for robust speech recognition. Especially, we propose the weighted function of asymmetric glottal pulse shape. which is used for weighted cepstrum extracted by PLP(Perceptual Linear Predictive) based on auditory model. Also, we analyze this glottal weighted cepstrum from the glottal pulse of glottal model in connection with the cepstrum. And we obtain speech features analyzed by both the glottal model and the auditory model. The isolated-word recognition rate is adopted for the test of proposed method in the car moise and street environment. And the performance of glottal weighted cepstrum is compared with both that of weighted cepstrum extracted by LP(Linear Prediction) and that of weighted cepstrum extracted by PLP. The result of computer simulation shows that recognition rate of the proposed glottal weighted cepstrum is better than those of other weighted cepstrums.

  • PDF

A New Pattern Classification and the Analysis of the Lung Sound by Using Cepstrum (Cepstrum을 이용한 폐음의 분석 및 패턴 분류)

  • 김종원;김성환
    • Journal of Biomedical Engineering Research
    • /
    • v.15 no.2
    • /
    • pp.159-166
    • /
    • 1994
  • A new pattern classification algorithm using cepstrum to analyze lung sounds for the classification of pattern with pulmonary and bronchial disorders is proposed. To evaluate the perfomance of the proposed method, the results are compared to the pattern classification with the AR modeling method. In the experiment lung sounds recorded for the training of physician used. As a results, the accuracy of the cepstrum classification is 92.3 % and AR modeling is the 53.8 %, therefore cepstrum modeling method has very high performance than AR and it turned out to be a very efficient algorithm.

  • PDF

A new Implementation of Perceptual LPC Cepstrum and its Application to Speech Recognition (인지 LPC cepstrum의 새로운 구현 및 음성인식에의 적용)

  • Kim, Jin-Young;Choi, Seong-Ho
    • The Journal of the Acoustical Society of Korea
    • /
    • v.15 no.5
    • /
    • pp.61-64
    • /
    • 1996
  • To improve the performance of a recognition system, namely the recognition rate, we propose a hew implementation of perceptual distance using LPC cepstrum(perceptual cepstrum, PLC). The PLC is caculated by convolution of a usual LPC cepstrum and a perceptual lifter(PL). To caculate PL, we define a new weighting function in the linear frequency domain considering the frequency scale(Bark-scale) characteristics. The PL is the inverse Fourier transform of the exponents of the weighting function. We verified our method through the speech recognition experiments. The performance of PLC was compared with that of the rasied sine liftering method.

  • PDF

On a robust text-dependent speaker identification over telephone channels (전화음성에 강인한 문장종속 화자인식에 관한 연구)

  • Jung, Eu-Sang;Choi, Hong-Sub
    • Speech Sciences
    • /
    • v.2
    • /
    • pp.57-66
    • /
    • 1997
  • This paper studies the effects of the method, CMS(Cepstral Mean Subtraction), (which compensates for some of the speech distortion. caused by telephone channels), on the performance of the text-dependent speaker identification system. This system is based on the VQ(Vector Quantization) and HMM(Hidden Markov Model) method and chooses the LPC-Cepstrum and Mel-Cepstrum as the feature vectors extracted from the speech data transmitted through telephone channels. Accordingly, we can compare the correct recognition rates of the speaker identification system between the use of LPC-Cepstrum and Mel-Cepstrum. Finally, from the experiment results table, it is found that the Mel-Cepstrum parameter is proven to be superior to the LPC-Cepstrum and that recognition performance improves by about 10% when compensating for telephone channel using the CMS.

  • PDF

On a Reduction of Computation Time of FFT Cepstrum (FFT 켑스트럼의 처리시간 단축에 관한 연구)

  • Jo, Wang-Rae;Kim, Jong-Kuk;Bae, Myung-Jin
    • Speech Sciences
    • /
    • v.10 no.2
    • /
    • pp.57-64
    • /
    • 2003
  • The cepstrum coefficients are the most popular feature for speech recognition or speaker recognition. The cepstrum coefficients are also used for speech synthesis and speech coding but has major drawback of long processing time. In this paper, we proposed a new method that can reduce the processing time of FFT cepstrum analysis. We use the normal ordered inputs for FFT function and the bit-reversed inputs for IFFT function. Therefore we can omit the bit-reversing process and reduce the processing time of FFT ceptrum analysis.

  • PDF

Speaker Recognition using LPC cepstrum Coefficients and Neural Network (LPC 켑스트럼 계수와 신경회로망을 사용한 화자인식)

  • Choi, Jae-Seung
    • Journal of the Korea Institute of Information and Communication Engineering
    • /
    • v.15 no.12
    • /
    • pp.2521-2526
    • /
    • 2011
  • This paper proposes a speaker recognition algorithm using a perceptron neural network and LPC (Linear Predictive Coding) cepstrum coefficients. The proposed algorithm first detects the voiced sections at each frame. Then, the LPC cepstrum coefficients which have speaker characteristics are obtained by the linear predictive analysis for the detected voiced sections. To classify the obtained LPC cepstrum coefficients, a neural network is trained using the LPC cepstrum coefficients. In this experiment, the performance of the proposed algorithm was evaluated using the speech recognition rates based on the LPC cepstrum coefficients and the neural network.

Cepstrum PDF Normalization Method for Speech Recognition in Noise Environment (잡음환경에서의 음성인식을 위한 켑스트럼의 확률분포 정규화 기법)

  • Suk Yong Ho;Lee Hwang-Soo;Choi Seung Ho
    • The Journal of the Acoustical Society of Korea
    • /
    • v.24 no.4
    • /
    • pp.224-229
    • /
    • 2005
  • In this paper, we Propose a novel cepstrum normalization method which normalizes the probability density function (pdf) of cepstrum for robust speech recognition in additive noise environments. While the conventional methods normalize the first- and/or second-order statistics such as the mean and/or variance of the cepstrum. the proposed method fully normalizes the statistics of cepstrum by making the pdfs of clean and noisy cepstrum identical to each other For the target Pdf, the generalized Gaussian distribution is selected to consider various densities. In recognition phase, we devise a table lookup method to save computational costs. From the speaker-independent isolated-word recognition experiments, we show that the Proposed method gives improved Performance compared with that of the conventional methods, especially in heavy noise environments.

EFFICIENCY OF SPEECH FEATURES (음성 특징의 효율성)

  • 황규웅
    • Proceedings of the Acoustical Society of Korea Conference
    • /
    • 1995.06a
    • /
    • pp.225-227
    • /
    • 1995
  • This paper compared waveform, cepstrum, and spline wavelet features with nonlinear discriminant analysis. This measure shows efficiency of speech parametrization better than old linear separability criteria and can be used to measure the efficiency of each layer of certain system. Spline wavelet transform has larger gap among classes and cepstrum is clustered better than the spline wavelet feature. Both features do not have good property for classification and we will compare Gabor wavelet transform, Mel cepstrum, delta cepstrum, etc.

  • PDF