The wigner distribution in speech processing applications

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Abstract

Recently the Wigner distribution has been shown to be a potentially useful tool for analysing the time varying frequency domain phenomenon. In this paper, some of the salient features of the Wigner distribution are presented; properties of this important discrete distribution are derived, and an efficient digital implementation is presented. Effective Wigner throughput rates, in excess of those obtainable with an equivalent length FFT, are shown to be feasible. In particular, the Wigner distribution is studied in the context of enhancing speech analysis and recognition systems. It is suggested that this class of distribution is consistent with the mechanics of human speech and, using experimentation, produces a very robust spectral signature. This enriched data space can be used to uncover some frequency domain attributes of human speech which may be lost using a discrete Fourier transform.

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This work was supported under NSF Grants ISI-8020634 and ECS-8001771 and 8313552.

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