Residual Lsf Vector Quantization Using Arma Prediction

Year 2016, Special Issue (2016), 79 - 81, 01.12.2016

Selma Ozaydin

Abstract

The
residual LSF vector quantization yields bit rate reduction in the vocoders. In
this work, a residual LSF vector quantization obtained from Auto Regressive
Moving Average (ARMA) prediction is proposed for designing codebooks at very
low bit rates. This residual quantization method is applied to multi stage
vector quantization method and codebooks are designed. For each codebook, the
effectiveness and quality are investigated by calculating the spectral
distortion and outliers. The proposed quantization method reduced the
distortion without any additional complexity.

Keywords

very low bit rate, speech processing, residual vector quantization, formant tracking, ARMA prediction

References

• A.V. McCree and T.P. Barnwell III, “ A Mixed Excitation LPC Vocoder Model for Low Bit Rate Speech Coding”, IEEE Transactions on Speech and Audio Processing, Vol.3, No.4, pp.242-250, July 1995
• W.P. LeBlanc, B.Bhattacharya, S.A. Mahmoud, “Efficient Search and Design Procedures for Robust Multi Stage Vector Quantization of LPC Parameters for 4 kbps Speech Coding”, IEEE Trans. on Speech and Audio Processing, Vol.1, No.4, pp.373-385, Oct., 1993
• I.T.Lim, B.G. Lee, “Lossless pole-zero modelling of speech signals”, IEEE Transactions on Speech, Signal and Audio processing, Vol.1, No.3, pp.269-276, July, 1993
• S. Ozaydin, B. Baykal, “Matrix quantization based linear predictive speech coding at very low bit rates”, Speech Communication, Vol. 41, Issues 2-3, pp:381-392, Oct. 2003
• S. Nandkumar, K. Swaminathan, U. Bhaskar, “Robust Speech Model based LSF Vector Quantization for Low Bit Rate Speech Coders”, in Proc. IEEE Int. Conf. Acoustics, Speech, Signal Processing, Vol.1, pp.41-44, May 1998
• J. Skoglund, J. Lindén, “Predictive VQ for noisy channel spectrum coding : AR or MA?” , Proc. IEEE Int. Conf. on Acoustics, Speech, Signal Processing, May, 1996
• J.R. de Marca, “An LSF quantizer for the North-American Half-Rate Speech Coder”, IEEE Transactions on Vehicular Technology, Vol.43, No.3, August, 1994
• H. Ohmuro, T. Moriya, K. Mano, and S. Miki, “Vector quantization of LSP parameters using moving average interframe prediction”, Electronics and Communications in Japan, Part 3, Vol.77, pp.12-26, 1994
• B. Wahberg, “ARMA spectral estimation of narrow band processes via model reduction”, IEEE Transactions on Acoustics, Speech and Signal Processing, vol. 38, July, 1990
• M.G. Kang, B.G. Lee, “A generalized vocal tract model for pole-zero type prediction”, Proc. Int.Conf. on ASSP, S14, 10, 1988
• L. Deng, L.J. Lee, etc, “Adaptive Kalman filtering and smoothing for tracking vocal tract resonances using a continuous valued hidden dynamic model”, IEEE Transactions on Audio, Speech and Language Processing, Vol.15, No.1, 2007