The speech-compression and expansion system involves the application of recent video data compression techniques to speech data. In order to effectively apply these techniques, the speech data should be segmented so as to achieve a high degree of correlation between corresponding samples and adjacent speech segments, allowing the formation of a two-dimensional speech "raster" with significant correlation in both dimensions. A method for generating such a two-dimensional format involves applying a hybrid cosine-transform/DPCM compression algorithm, as described by Habibi et al, "Real-Time Image Redundancy Reduction Using Transform Coding Techniques," IEEE 1974 International Conference on Communications, Record, Minneapolis, Minn., June 1974, pp. 18A1-18A8.
Traditionally, speech has been regarded as a one-dimensional time series, while television data has been regarded as a two-dimensional random process with correlation in both dimensions which can be exploited for data compression. In order to exploit well-developed two-dimensional compression algorithms and coding technology and also to visually study the structure of speech data, such data is presented herein as a series of television images with 256 levels of grey. The middle grey level, #128, is chosen to represent zero amplitude, while the white and black extreme levels are chosen to represent negative and positive maximum speech amplitudes, respectively.
Several types of transforms have been proposed and evaluated for use in video bandwidth reduction systems. These transforms have been described by Habibi et al, in the article described hereinabove. Among these are included the Karhunem-Loeve (K-L) transform, the Fourier transform, the cosine transform, the Hadamard, Walsh transform, and the slant transform.
Until recently, however, only one of these has been used with any success in the processing of speech data. This transform, the Fourier transform, along with its close logarithmic "cousins", has been used extensively in the implementation of Vocoder-type speech compression systems. These types of systems have been described by Rabiner, L. R. and B. Gold, "Theory and Applications of Digital Signal Processing," Prentice-Hall, N.J., 1975, pp. 687-691; Oppenheim, A. V. and R. W. Scheefer, "Digital Signal Processing," Prentice-Hall, N.J., 1975, pp. 518-520; and Bayless, J. W., S. J. Campanella, and A. J. Goldberg, "Voice Signals, Bit by Bit," IEEE Spectrum, October 1973, pp. 28-34.
As with video data, however, it is very likely that the redundant information in speech is more efficiently revealed via linear transforms more nearly like the K-L transform than the Fourier transform is, particularly when the length of the data block being transformed is small relative to a few hundred periods of the highest frequency component of interest.
The family of cosine transforms have this feature, in that they more nearly represent the optimum transform for revealing the redundancy of two-dimensional data than any of the other transforms listed (with the exception of the K-L transform, which is not amenable to as simple an implementation).
Cosine transforms for data compression can be implemented with discrete algorithms operating on sampled data. When sampling is assumed, then the resulting cosine transforms can be classified as "even" (EDCT), "odd" (ODCT), or "mixed" (MDCT).
These first two have been thoroughly discussed by Speiser, J. M., "High Speed Serial Access Implementation for Discrete Cosine Transforms," NUC TN 1265, Jan 8, 1974; and Whitehouse, H. J., R. W. Means and J. M. Speiser, "Signal Processing Architectures Using Transversal Filter Technology," 1975 IEEE International Symposium on Circuits and Systems Proceedings, Boston, April 1975. A brief general discussion of the discrete cosine transforms appears in the patent to Speiser, et al, entitled APPARATUS FOR PERFORMING A DISCRETE COSINE TRANSFORM OF AN INPUT SIGNAL, having the No. 4,152,772, dated May 1, 1979.
A paper, dealing with the general subject matter of this invention, has been presented by the co-inventors at the 1978 IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP), (April 1978), under the title of "Two-Dimensional Speech Compression".
The application of the EDCT algorithm has only just recently been demonstrated by the inventors for speech data compression. The ODCT and MDCT algorithms have not yet been tried.