Linear predictive coding

About: Linear predictive coding is a research topic. Over the lifetime, 6565 publications have been published within this topic receiving 142991 citations. The topic is also known as: Linear predictive coding, LPC.

Formant location from LPC analysis data

Abstract: The estimation of formant frequencies and bandwidths from the filter coefficients obtained through linear-predictive-coding (LPC) analysis of speech is discussed from several viewpoints. A method for locating roots within the unit circle is derived. This algorithm is particularly well suited to computations carried out in fixed-point arithmetic using specialized signal processing hardware. >

A fixed point computation of partial correlation coefficients

Abstract: This paper introduces a new computational algorithm for the partial correlation coefficients of a linear system given the covariance of its output when excited by a white input noise. Although derived from Levinson's well-known procedure, the proposed algorithm does not make use of the usual parameters in the linear prediction recursion. It may be implemented using fixed point arithmetics. Application to speech waves is emphasized.

Note on the properties of a vector quantizer for LPC coefficients

Abstract: Vector quantization has been used in coding applications for several years. Recently, quantization of linear predictive coding (LPC) vectors has been used for speech coding and recognition. In these latter applications, the only method that has been used for deriving the vector quantizer code book from a set of training vectors is the one described by Linde, Buzo, and Gray. In this paper, we compare this algorithm to several alternative algorithms and also study the properties of the resulting code books. Our conclusion is that the various algorithms that we tried gave essentially identical code books.

Pitch modification of speech using a low-sensitivity inverse filter approach

Abstract: A simple and effective method for modifying the pitch of recorded speech units is described This method was developed to overcome some limitations in the promising residual-excited linear prediction (RELP) technique The key difference is that the choice of filter parameters in the new method is driven by a need for reducing sensitivity to pitch modification, rather than creating a residual with minimum energy as in RELP Speech modifications using this method are superior in quality to those obtained with RELP, while at the same time being less sensitive than RELP to errors in pitch marking

Methods and apparatus for noise conditioning in digital speech compression systems using linear predictive coding

Abstract: In methods and apparatus for processing a speech signals comprising a plurality of successive signal intervals, each signal interval containing no speech sounds is classified as a noise interval, and LPC coefficients are calculated for each noise interval based on the samples of that noise interval and on the samples of a plurality of preceding signal intervals. When noise intervals encoded using LPC coefficients calculated as described above are reconstructed, the subjectively annoying "swishing" or "waterfall" effects encountered in conventional LPC speech processing systems are reduced or eliminated.