Abstruct-Linear predictive coding (LPC) parameters are widely used in various speech processing applications for representing the spectral envelope information of speech. For low bit rate speech-coding applications, it is important to quantize these parameters accurately using as few bits as possible. Though the vector quantizers are more efficient than the scalar quantizers, their use for accu...

This thesis introduces a novel method for accurate pitch detection and speech segmentation, named Multi-feature, Autocorrelation (ACR) and Wavelet Technique (MAWT). MAWT uses feature extraction, and ACR applied on Linear Predictive Coding (LPC) residuals, with a wavelet-based refinement step. MAWT opens the way for a unique approach to modeling: although speech is divided into segments, the suc...

From this perspective, the core attribute of PC is the de-linking of volume and cost, while maintaining or improving quality. But there are other valuable perspectives on PC. At first glance, the range of available PC systems and solutions is bewildering. A closer look reveals that the landscape is governed by a small number of structural choices—choices posed by the problems that predictive co...

Vector quantization is a powerful tool for speech coding applications. This paper deals with LPC Coding of speech signals which uses a new technique called Multi Switched Split Vector Quantization (MSSVQ), which is a hybrid of Multi, switched, split vector quantization techniques. The spectral distortion performance, computational complexity, and memory requirements of MSSVQ are compared to spl...

This paper proposes a low bit rate coding method for speech and audio using a new analysis method named MLPC (Mel-LPC analysis). In the MLPC analysis method a spectrum envelope is estimated on a melor bark-frequency scale, so as to improve the spectral resolution in the low frequency band. This analysis is accomplished with about two-fold increase in computation over the standard LPC analysis. ...

In this paper linear prediction process is applied to frequency warped signals. The warping is realized by using orthonormal FAM' functions. The general formulation of WLP is given and effective realizations with allpass filters are studied. The application of auditory WLP to speech coding and speech recognition has given good results.

A new criterion is derived for the design of the noise weighting filter in linear predictive coding (LPC) that accounts for the issue of noise propagation. It will be shown that the new filter design constitutes an approximation of the reverse waterfilling procedure known from rate-distortion theory and audio transform coding. It improves the overall coding SNR of closed-loop LPC with noise sha...

Speech coding techniques commonly used in low bit rate analysis-by-synthesis linear predictive coders (LPAS coders) create a model that emphasizes the important features of a speech signal. The utilization of these coding methods for speech enhancement is shown. Specifically, the speech signal will be modeled as the output of a cascade of an adaptive formant filter and an adaptive pitch filter,...

Background environmental noises degrade the performance of speech-processing systems (e.g. speech coding, speech recognition). By modifying the processing according to the type of background noise, the performance can be enhanced. This requires noise classification. In this work, four pattern-recognition frameworks have been used to design noise classification algorithms. Classification is done...

Previous work in wireless speech recognition has focused on two methods, namely, quantizing recognition features (e.g. MFCC) or performing recognition using speech coding parameters (e.g. LPC). All of this previous research assumes that the communication channel is only large enough to transmit either speech coding parameters or speech recognition parameters. By contrast, we propose that the sp...