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.

Method and apparatus for variable rate coding of speech

Abstract: A speech encoding method using analysis-by-synthesis includes sampling an input speech and dividing the resulting speech samples into frames and subframes. The frames are analyzed to determine coefficients for the synthesis filter. The subframes are categorized into unvoiced, voiced and onset categories. Based on the category, a different coding scheme is used. The coded speech is fed into the synthesis filter, the output of which is compared to the input speech samples to produce an error signal. The coding is then adjusted per the error signal.

An interpretation of the log likelihood ratio as a measure of waveform coder performance

Abstract: The log likelihood measure has been widely used in speech research for comparing speech signals. Recently, it has been proposed as a measure for assessing the quality of coded speech. In this paper we present an interpretation of the log likelihood ratio measure within the theoretical framework of a waveform coder distortion model. We then discuss the implications of this interpretation and show how it can be applied to the formulation of better objective measures of waveform coder performance.

A new variable frame analysis method for speech recognition

Abstract: Variable frame rate (VFR) analysis is a technique used in speech processing and recognition for discarding frames that are too much alike. The article introduces a new method for VFR. Instead of calculating the distance between frames, the norm of the derivative parameters is used in deciding to retain or to discard a frame, informal inspection of speech spectrograms shows that this new method puts more emphasis on the transient regions of the speech signal. Experimental results with a hidden Markov model (HMM) based system show that the new method outperforms the classical method. >

A multi-band CELP wideband speech coder

Abstract: A novel low-delay wideband speech coder, called multiband CELP (MB-CELP), overcomes the major obstacles usually associated with two traditional CELP approaches to wideband speech coding-namely fullband CELP and split-band CELP. The new MB-CELP coder employs a multi-band bank of off-line filtered excitation codebooks, fullband linear prediction synthesis, and minimization of the error between the original and the synthesized speech signal over the full frequency range. A 16 kbps version of the MB-CELP coder with two equal bands, is described. Subjective comparison test results show that this coder performs better than the G.722 coder at a bit-rate of 48 kbps.

Estimation of subband speech correlations for noise reduction via MVDR Processing

Abstract: Recently, it has been proposed to use the minimum-variance distortionless-response (MVDR) approach in single-channel speech enhancement in the short-time frequency domain. By applying optimal FIR filters to each subband signal, these filters reduce additive noise components with less speech distortion compared to conventional approaches. An important ingredient to these filters is the temporal correlation of the speech signals. We derive algorithms to provide a blind estimation of this quantity based on a maximum-likelihood and maximum a-posteriori estimation. To derive proper models for the inter-frame correlation of the speech and noise signals, we investigate their statistics on a large dataset. If the speech correlation is properly estimated, the previously derived subband filters discussed in this work show significantly less speech distortion compared to conventional noise reduction algorithms. Therefore, the focus of the experimental parts of this work lies on the quality and intelligibility of the processed signals. To evaluate the performance of the subband filters in combination with the clean speech inter-frame correlation estimators, we predict the speech quality and intelligibility by objective measures.