Restoration of Nonlinearly Distorted Audio by Histogram Equalization

White SA. Restoration of Nonlinearly Distorted Audio by Histogram Equalization. In: AES Convention 69. Audio Engineering Society; 1981. Paper 1764. Available from: https://aes.org/publications/elibrary-page/?id=11989

@inproceedings{White1981_11989,
  author = {White, Stanley A.},
  title = {{Restoration of Nonlinearly Distorted Audio by Histogram Equalization}},
  booktitle = {AES Convention 69},
  note = {Paper 1764},
  year = {1981},
  month = may,
  publisher = {Audio Engineering Society},
  url = {https://aes.org/publications/elibrary-page/?id=11989}
}

TY  - CPAPER
TI  - Restoration of Nonlinearly Distorted Audio by Histogram Equalization
AU  - White, Stanley A.
T2  - AES Convention 69
M1  - Paper 1764
PY  - 1981
DA  - 1981/05/06
UR  - https://aes.org/publications/elibrary-page/?id=11989
PB  - Audio Engineering Society
LA  - en
AB  - Restoration of degraded speech which has been captured on audio tape often relies on linear adaptive-filtering procedures or their hardware embodiments such as the Rockwell ADAP. If the speech degradation can be modeled by a linear process, then liner adaptive filtering can provide suitable restoration. If, however, a nonlinear phenomenon, such as soft saturation, has been a contributor to the degradation, then the linear adaptive filter is no longer adequate. Linear adaptive filters consist of one or more transversal and/or recursive sections whose tap weights or gains are linear and whose values are adjusted so that the filter minimizes a performance criterion in some prescribed sense, such as minimum mean-squared error. A more general form of adaptive filter is proposed, one in which the gain at each tap location is a function of the signal at that tap. Next, this new filter is approximated by an alternating sequence of short linear adaptive filters which perform frequency-domain equalization, and nonlinear amplitude correctors which perform amplitude-domain equalization. Preliminary experiments have been performed using the nonlinear corrector portion of this new class of adaptive filter. Histogram equalization is used to define the nonlinear-gain strategy. The training to obtain the reference histogram for histogram equalization is remarkably speaker invariant when proper techniques are used for modeling. Sample audio tapes will be played to demonstrate the results which have been obtained by this technique.
ER  -