Nonlinear Long-Term Prediction of Speech Signal(Regular Section)

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概要

• 論文の詳細を見る

• This letter addresses a neural network (NN)-based predictor for the LP (Linear Prediction) residual. A new NN predictor takes into consideration not only prediction error but also quantization effects. To increase robustness against the quantization noise of the nonlinear prediction residual, a constrained back propagation learning algorithm, which satisfies a Kuhn-Tucker inequality condition is proposed. Preliminary results indicate that the prediction gain of the proposed NN predictor was not seriously decreased even when the constrained optimization algorithm was employed.

• 社団法人電子情報通信学会の論文
• 2002-07-25

著者

• Lee Ki-seung

  Department Of Electronic Engineering Konkuk University

関連論文

• Effect of Equal Channel Angular Pressing on the Distribution of Reinforcements in the Discontinuous Metal Matrix Composites
• Voice Conversion Using Low Dimensional Vector Mapping(Regular Section)
• Robust Recognition of Fast Speech(Speech and Hearing)
• Nonlinear Long-Term Prediction of Speech Signal(Regular Section)

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