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Analysis of speech signals of short pitch period by a sample-selective linear prediction
The conventional linear prediction analysis has difficulties in estimating the vocal tract characteristics of voiced sounds uttered by females or children. This paper shows that the vocal tract characteristics of those speech signals can be estimated accurately by the sample-selective linear prediction (SSLP) method proposed by the authors. The SSLP is a two-stage linear prediction analysis employ...Show More
Estimation of anti-resonance frequencies by using an over-determined high-order Yule-Walker equation
ICASSP '86. IEEE International Conference on Acoustics, Speech, and Signal Processing
Year: 1986 | Conference Paper |
The over-determined Yule-Walker equation improves stability and accuracy of the linear prediction analysis. This report describes the effects of introducing over-determined Yule-Walker equation and parameter conversion in the frequency domain into the two-stage ARMA estimation. The simulation results proves that the proposed method is robust against window positioning and retains better analysis a...Show More
Analysis of speech signals of short pitch period by the sample-selective linear prediction
ICASSP '86. IEEE International Conference on Acoustics, Speech, and Signal Processing
Year: 1986 | Conference Paper |
Cited by: Papers (3)
The conventional linear prediction analysis has difficulties in estimating the vocal tract characteristics of voiced sounds uttered by females or children. In this paper, it is shown that the vocal tract characteristics of those speech signals can be estimated accurately by the sample-selective linear prediction(SSLP) method proposed by the authors. The SSLP is a two-stage linear prediction analys...Show More
Difference operation for Pre/Post-emphasis in linear prediction analysis
ICASSP '84. IEEE International Conference on Acoustics, Speech, and Signal Processing
Year: 1984 | Conference Paper |
The relationship between the predictors obtained on differenced data and those on original data is derived for both the covariance method and the auto-correlation method. The physical interpretation of the derived relationship is discussed in connection with spectral enhancement. The cause of the error of the relationship is analyzed from both system theoretic and practical points of view.Show More
A sample selective linear prediction analysis of speech
ICASSP '84. IEEE International Conference on Acoustics, Speech, and Signal Processing
Year: 1984 | Conference Paper |
The formulation of linear prediction analysis using the generalized inverse matrix is reviewed and Givens' reduction employing Gentleman's algorithm is introduced as a fast computational method to obtain the least-squares estimate for the prediction coeficients. An improved version of the sample selective linear prediction (SSLP) is described and some performance examples on nonstationary syntheti...Show More
Hierarchical AR model for time varying speech signals
ICASSP '82. IEEE International Conference on Acoustics, Speech, and Signal Processing
Year: 1982 | Conference Paper |
Cited by: Papers (10)
The auto-regressive(AR) model is adopted to the trajectories of speech feature parameters such as linear predictors and formant frequencies. The procedure is hierarchical in its structure and is expected to be suitable for the analysis of time varying speech or non-stationary parts of speech. The method is formulated in matrix form and a feature transition matrix is introduced to express the tempo...Show More
Speech analysis by selective linear prediction in the time domain
ICASSP '82. IEEE International Conference on Acoustics, Speech, and Signal Processing
Year: 1982 | Conference Paper |
Cited by: Papers (9)
Linear prediction method is one of the most frequently used analysis methods of speech. Covariance method and auto-correlation method of linear prediction often fail to make a precise analysis of speech because of the excitation source or fundamental frequency. In order to decrease the affect of the excitation source, various kinds of difference operations are usually employed for preprocessing. H...Show More
Least-squares method for multi-dimensional deconvolution
ICASSP '82. IEEE International Conference on Acoustics, Speech, and Signal Processing
Year: 1982 | Conference Paper |
Least-squares method is applied to multi-dimensional deconvolution or estimation of input waveforms to a multi-input multi-output system given the transfer characteristics of the system. Suppose a system accepts n-dimensional input s(t) and it produces m-dimensional output f(t). Let hij(t) be the impulse response of the channel from jth input terminal to ith output terminal. Using an m × n matrix ...Show More
Discrete Fourier transform based on a double-sampling and its applications
ICASSP '76. IEEE International Conference on Acoustics, Speech, and Signal Processing
Year: 1976 | Conference Paper |
An effective method for calculating the Discrete Fourier Transform (DFT) of a double-sampled sequence (a pair of the equi-interval-sampled sequences) is presented in a matrix form. The calculation formula shows that the DFT of a certain type of band-limited signals can be effectively evaluated from the DFT's of a pair of the equi-interval-sampled sequences of the signal. It is demonstrated that th...Show More
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