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Speech Coding

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TLDR
The performance of a one-bit digital matched i t e r (DMF) responding to binary signaling through a noisy multipath channel is analyzed and the output signal-to-noise ratio (SNR,) plays a key role in the analysis.
Abstract
We analyze the performance of a one-bit digital matched i t e r (DMF) responding to binary signaling through a noisy multipath channel. The output signal-to-noise ratio (SNR,) plays a key role in the analysis. The S N b performance is fully studied for a two-path channel, both fading and non-fading. For the general N-path channel, results are obtained only for the fading case. All results are conditioned on the knowledge of the time delays of all paths, and are valid only for smaIl input signal-to-noise ratio (SNRi). Most of the results have been verified by computer simulations.

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References
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TL;DR: This paper gives an exposition of linear prediction in the analysis of discrete signals as a linear combination of its past values and present and past values of a hypothetical input to a system whose output is the given signal.
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Quantizing for minimum distortion

TL;DR: This paper discusses the problem of the minimization of the distortion of a signal by a quantizer when the number of output levels of the quantizer is fixed and an algorithm is developed to simplify their numerical solution.
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Speech analysis and synthesis by linear prediction of the speech wave.

TL;DR: Application of this method for efficient transmission and storage of speech signals as well as procedures for determining other speechcharacteristics, such as formant frequencies and bandwidths, the spectral envelope, and the autocorrelation function, are discussed.
Journal ArticleDOI

Cepstrum Pitch Determination

TL;DR: Algorithms were developed heuristically for picking those peaks corresponding to voiced‐speech segments and the vocal pitch periods, which were then used to derive the excitation for a computer‐simulated channel vocoder.
Journal ArticleDOI

A comparative performance study of several pitch detection algorithms

TL;DR: A comparative performance study of seven pitch detection algorithms was conducted, consisting of eight utterances spoken by three males, three females, and one child, to assess their relative performance as a function of recording condition, and pitch range of the various speakers.