Conventional Linear Predictive Coding Research Articles

Compression of 3D mesh sequences by temporal segmentation

ABSTRACTWe describe a compression method for three‐dimensional animation sequences that has notable advantages over existing techniques. We first aggregate the frame data by similarity and reorganize them into clusters, which results in the sequence split into several motion fragments of varying lengths. To minimize the number of clusters and obtain optimal clustering, we perform frame alignment, which eliminates the “global” rigid transformation from each frame data and use only “pose” when evaluating the similarity between frames. We then apply principal component analysis for each cluster, from which we get coordinates of corresponding frames in a reduced dimension. Because similar frames are considered, the number of coefficients required for each frame becomes smaller; thus, we obtain better dimension reduction for a given reconstruction error. Further, we perform intracluster compression based on linear coding. Because every motion fragment presents similar frames, conventional linear predictive coding can be replaced by key frame‐based linear coding to achieve minimal reconstruction error. Results show that our method can obtain a high compression ratio, with a limited reconstruction error. Copyright © 2013 John Wiley & Sons, Ltd.

A comparison of warped and conventional linear predictive coding

Frequency-warped signal processing techniques are attractive to many wideband speech and audio applications since they have a clear connection to the frequency resolution of human hearing. A warped version of linear predictive coding (LPC) is studied. The performance of conventional and warped LPC algorithms are compared in a simulated coding system using listening tests and conventional technical measures. The results indicate that the use of warped techniques is beneficial especially in wideband coding and may result in savings of one bit per sample compared to the conventional algorithm while retaining the same subjective quality.

LPC analysis incorporating spectral interpolation for speech coding

A linear predictive coding (LPC) analysis scheme which is applicable to speech coding is proposed. The analysis method, called interpolative LPC (ILPC) analysis, estimates the spectral envelope by incorporating the interpolation characteristics into the LPC analysis. The ILPC analysis reduces average spectral distortion and the percentage of outlier frames, compared with the conventional LPC analysis followed by linear interpolation.

Multiscale fourier descriptors for classifying semivowels in spectrograms

Fourier descriptors (FDs) have been used successfully to characterize the boundary of objects in images. It is demonstrated that FDs are appropriate for characterizing objects in speech spectrograms consisting of 40 sounds representing 10 speaker-dependent words containing the English semivowels /w y l r/. With 10 FDs, a 97.5% recognition rate is attained. Different sounds are misclassified by wide- and narrow-band methods, suggesting that multiscaling and FD changes (differences) may be appropriate features. With a FD difference approach, recognition rates equaled or exceeded those obtained with a conventional linear predictive coding (LPC) classifier as well as those obtained with wide- and narrow-band FD methods alone.

Decomposition of the LPC excitation using the zinc basis functions

A linear predictive coding (LPC) excitation signal composed of a set of orthogonal functions called zinc functions is introduced. These functions are shown to form a complete orthogonal set and have properties that are well suited for modeling the LPC residual signal. A benchmark comparison between Fourier series and zinc function modeling shows that the zinc function model for the residual is superior in the mean-squared-error sense. The zinc basis functions are used in two low-bit-rate speech coding systems targeted at the 4.8-9.6-kb/s range. The first is a zinc excited LPC (ZELPC) system, where the voiced excitation is modeled using the zinc functions while the unvoiced excitation is represented by the usual white noise source. The second system is a zinc multipulse LPC (ZMPLPC) system, where the LPC excitation is constructed using the zinc basis functions instead of the usual ideal impulses. Results show that, given a fixed segmental signal-to-noise ratio with similar computational complexity, the ZMPLPC system is more efficient than a conventional multipulse LPC (MPLPC) system. Subjective listening tests also indicate a preference for the ZMPLPC system. >

On the effects of varying filter bank parameters on isolated word recognition

The vast majority of commercially available isolated word recognizers use a filter bank analysis as the front end processing for recognition. It is not well understood how the parameters of different filter banks (e.g., number of filters, types of filters, filter spacing, etc.) affect recognizer performance. In this paper we present results of performance evaluation of several types of filter bank analyzers in a speaker trained isolated word recognition test using dialed-up telephone line recordings. We have studied both DFT (discrete Fourier transform) and direct form implementations of the filter banks. We have also considered uniform and nonuniform filter spacings. The results indicate that the best performance (highest word accuracy) is obtained by both a 15-channel uniform filter bank and a 13-channel nonuniform filter bank (with channels spacing along a critical band scale). The performance of a 7-channel critical band filter bank is almost as good as that of the two best filter banks. In comparison to a conventional linear predictive coding (LPC) word recognizer, the performance of the best filter bank recognizers was, on average, several percent worse than that of an eighth-order LPC-based recognizer. A discussion as to why some filter banks performed better than others, and why the LPC-based system did the best, is given in this paper.

On the effects of varying filter bank parameters on isolated word recognition

The vast majority of commercially available isolated word recognizers use a filter bank analysis as the front end processing for recognition. It is not well understood how the parameters of different filter banks (e.g., number of filters, types of filters, filter spacing, etc.) affect recognizer performance. In this talk we present results of performance evaluation of several types of filter bank analyzer in a speaker trained, isolated word recognition test using dialed‐up telephone line recordings. We have studied both DFT (discrete Fourier transform) and direct form implementations of the filter banks. We have also considered uniform and nonuniform filter spacings. The results indicate that the best performance (highest word accuracy) is obtained by both a 15‐channel uniform filter bank and a 13‐channel nonuniform filter bank (with channels spaced along a critical band scale). In comparison to a conventional linear predictive coding (LPC) word recognizer, the performance of the best filter bank recognizers was, on average, several percent worse than that of an eighth order LPC‐based recognizer.

Tandem Connections of Wideband and Narrowband Speech Communications Systems: Part 1-Narrowband-to-Wideband Link

The performance of a tandem connection of narrowband and wideband speech communication systems is evaluated. Specifically, the narrowband system consists of a conventional linear Predictive Coding (lpc) vocoder operating at a bit-rate of 2.4 kb/s and the wideband system consists of a Continuously Variable Slope Delta modulator cvsd operating at a bit rate of 16 kb/s. In Part 1 of this paper the properties of the narrowband-to-wideband link are investigated and in Part 2 the properties of the wideband-to-narrowband link are investigated. In part 1 the snr (signal-to-quantizing noise ratio) of the cvsd coder is analyzed over a 50-dB variation of the input signal levels and for a variety of source excitations for the lpc synthesizer. It is shown that snr improvements in the cvsd coder of 2 to 2.5 dB are possible in the slope overload region of the coder by modifying the source excitation of the lpc synthesizer and by preprocessing the input signal to the coder with an allpass filter. Both methods aid in reducing the peak factor (peak-to-rms level) of the input speech to the coder. Subjectively, however, only slight improvements in quality, if any, were observed with these modifications.