Title :
Noncausal ARMA modeling of voiced speech
Author :
Jackson, Leland B.
Author_Institution :
Dept. of Electr. Eng., Rhode Island Univ., Kingston, RI, USA
fDate :
10/1/1989 12:00:00 AM
Abstract :
A noncausal autoregressive moving average (ARMA) source-filter model of voiced speech is proposed. Although the human speech-production mechanism is obviously causal, a noncausal model allows the simple source-filter approach to incorporate different parameters for the open-glottis and closed glottis portions of the pitch period (without explicit determination of the open- and closed-glottis regions). The noncausal impulse response is obtained by standard cepstral deconvolution. Separate ARMA models are then found for the causal and anticausal portions of the impulse response. Initial experiments show that very close approximations to the speech waveform and spectrum are produced by two twelfth-order ARMA models
Keywords :
encoding; filtering and prediction theory; speech analysis and processing; ARMA models; LPC; cepstral deconvolution; closed glottis; human speech-production mechanism; linear predictive coding; noncausal autoregressive moving average; noncausal impulse response; open-glottis; pitch period; source-filter model; speech spectrum; speech waveform; twelfth-order ARMA models; voiced speech; Autocorrelation; Cepstral analysis; Cepstrum; Deconvolution; Humans; Information filtering; Information filters; Linear predictive coding; Speech analysis; Speech coding;
Journal_Title :
Acoustics, Speech and Signal Processing, IEEE Transactions on