This paper describes a multiband vector quantization (VQ) technique based on inner product for wideband speech coding at 16 kb/s. Our approach consists of splitting the input speech into two separate bands and then applying an independent coding scheme for each band. A code excited linear prediction (CELP) coder is used in the lower band while a transform based coding strategy is applied in the higher band. The spectral components in the higher frequency band are represented by a set of modulated lapped transform (MLT) coefficients. The higher frequency band is divided into three subbands, and the MLT coefficients construct a vector for each subband. Specifically, for the VQ of these vectors, an inner product-based distance measure is proposed as a new strategy. The proposed 16 kb/s coder with the inner-product based distortion measure achieves better performance than the 48 kb/s ITU-T G.722 in subjective quality tests.

A new type of analog-to-digital (A/D) converter is introduced. The structure is based on a magnitude-preserving quadrature mirror filter (QMF) bank where the analysis bank is composed on IIR switched-capacitor (SC) filters. The analog output samples of the analysis filters are converted into digital form using individual A/D converters and combined by an IIR digital filter synthesis filter bank. This A/D converter is useful in applications where only the magnitude of the spectrum of the analog signal needs to be preserved. The structure incorporates the advantages of sub-band coding and reduces considerably the effect of mismatches among the sub-band A/D converters. In addition, the proposed scheme leads to an increase in the conversion speed by a factor of M when an M-channel QMF bank is used. An illustrative example verifying the good performance of the proposed approach is included.

Most natural images are well modeled as smoothed areas segmented by edges. The smooth areas can be well represented by a wavelet transform with high regularity and with fewer coefficients which requires highpass filters with some vanishing moments. However for the regions around edges, short highpass filters are preferable. In one recently proposed approach, this problem was solved by switching filter banks using longer filters for smoothed areas of the images and shorter filters for areas with edges. This approach was applied to lossy image coding resulting in a reduction of ringing artifacts. As edges were predicted using neighboring pixels, the nonlinear transforms made the decorrelation more flexible. In this paper we propose a time-varying filterbank and apply it to lossless image coding. In this scheme, we estimate the standard deviation of the neighboring pixels of the current pixel by solving the maximum likelihood problem. The filterbank is switched between three filter banks, depending on the estimated standard deviation.

This paper presents a new multistage comb-rotated sinc (RS) decimator with a sharpened magnitude response. Novelty of this paper is that the multistage structure has more design parameters that provides additional flexibility to the design procedure. It uses different sharpening polynomials and different cascaded comb filters at different stages. As the comb filters at the latter stages are of lower order than that of the original comb filter, the use of more complex sharpening polynomials at latter stages is possible. This leads to an improvement of the frequency characteristic without a significant increase in the complexity of the overall filter. The comb filter of the first stage is realized in a non-recursive form and can be implemented in a computationally efficient form by making use of the polyphase decomposition of the transfer function in which the subfilters operate at a lower rate that depends on the down-sampling factor employed in the first stage. In addition, both multipliers of the rotated sinc (RS) filter of the second stage work at a lower rate.

In this letter, we propose an approach to incorporate a statistical model for the voiced/unvoiced (V/UV) speech decision under background noise environments. Our approach consists of splitting the input noisy speech into two separate bands and applying a statistical model for each band. We compute and compare the likelihood ratio (LR) for each band based on the statistical model and estimated noise statistics for the V/UV decision. According to the simulation test, the proposed V/UV decision shows a better performance compared with the selectable mode vocoder (SMV) V/UV decision algorithm, particularly in clean and white noise environments.