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- W2137720729 abstract "We present a new speech coding algorithm, based on an all-pole model of the vocal tract. Whereas current autoregressive (AR) based modeling techniques (e.g. CELP, LPC-10) minimize a prediction error, which is considered to be the input to the all-pole model, our approach determines the closest (in L/sub 2/ norm) signal, which exactly satisfies an all-pole model. Each frame is then encoded by storing the parameters of the complex damped exponentials deduced from the all-pole model and its initial conditions. Decoding is performed by adding the complex damped exponentials based on the transmitted parameters. The new algorithm is demonstrated on a speech signal. The quality is compared with that of a standard coding algorithm at comparable compression ratios, by using the segmental signal-to-noise ratio (SNR)." @default.
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- W2137720729 date "2002-11-27" @default.
- W2137720729 modified "2023-10-18" @default.
- W2137720729 title "Speech compression based on exact modeling and structured total least norm optimization" @default.
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- W2137720729 doi "https://doi.org/10.1109/icassp.1998.674440" @default.
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