Low-delay hybrid vector excitation linear predictive speech coding

A hybrid approach in determining the excitation vector in a low-delay code excited linear predictive coder is proposed. By a judicious division of the composite excitation vector into long-term and short-term components, and the use of switched quantisation, substantial improvement in coding quality is obtained.<>     

CELP based mixed-source model for very low bit rate speech coding

A CELP based mixed-source model is described. It uses a mixed excitation which combines a lowpass-filtered adaptive source and a highpass-filtered stochastic source. In addition, one more stochastic source is newly employed for more natural sounding speech. In informal listening tests, the proposed model at 3 kbit/s shows very good performance both in speech quality and intelligibility.<>     

Reduced-delay quadrature mirror filter structures for subband coding of speech

In subband coding systems of speech, quadrature mirror filter (QMF) banks have been used effectively in a tree-structured form for decomposition and alias-free reconstruction of the speech signal. In the present paper, we derive some new causal and noncausal QMF structures which can reduce group delay. These structures are based on even- as well as odd-length finite impulse response filters.     

Low-delay vector excitation coding of speech at 16 kb/s

The need for a 16-kb/s speech coding algorithm that has very low coding delay while achieving essentially the same high quality as the 32-kb/s adaptive differential pulse code modulation (ADPCM) standard G.721 is addressed. The authors describe low-delay vector excitation coding (LD-VXC), a new coding algorithm which provides high quality with less than 2 ms of coding delay and is robust to transmission errors. The algorithm combines techniques such as vector quantization, analysis-by-synthesis, and perceptual weighting together with backward adaptive linear predictive encoding, and uses a novel long-term predictor employing backward adaptive pitch tracking. Perceptually based nose shaping and postfiltering contribute to the masking of audible quantization noise     

High-quality coding of telephone speech and wideband audio

Digital speech technology is reviewed, with the emphasis on applications demanding high-quality reproduction of the speech signal. Examples of such applications are network telephony, ISDN terminals for audio teleconferencing, and systems for the storage of audio signals, which include the important subclass of wideband speech. Depending on the application, the bandwidth of input speech can vary from about 3 kHz to nearly 20 kHz. Coding for digital telephony at 4 and 8 kb/s, network quality coding at 16 kb/s, and coding for audio at 7 and 20 kHz are examined. Future directions in the field are discussed with respect to anticipated technology applications and the algorithms needed to support these technologies     

Bandwidth extension of speech signals: a catalyst for the introduction of wideband speech coding?

The restricted audio quality of today's telephone networks is mainly due to the narrowband (NB) limitation to the frequency range from about 300 Hz to 3.4 kHz. Meanwhile, codecs for wideband (WB) telephony (50 Hz to 7 kHz) exist with significantly improved speech intelligibility and naturalness. However, the broad introduction of wideband speech coding requires strong efforts of both network operators and their customers because many elements of the networks (i.e., terminals and network nodes) have to be modified. An intermediate step to overcome the narrowband limitation can be achieved by applying artificial bandwidth extension (BWE) in the receiver. In this article we review the basic principles of bandwidth extension, and discuss several application scenarios in which both wideband coding and BWE complement each other. The introduction of BWE methods in terminals and networks may help to speed up the introduction of true wideband speech coding in the near future.     

Vector quantisation of wideband transform coefficient timetrajectories in speech coding

A number of methods to perform efficient dynamic bit allocation to perceptually important parameters in the frequency domain results from the combination of vector quantisation techniques and wideband transform coding. Time trajectories of transform coefficients and of magnitude and phase-derivative coefficients are used as vectors for vector quantisation. Speech coders implementable in single DSPs with external memory, having short delay and high robustness to bit stream distortions have been developed     

Regularized subband coding scheme

Two enhanced subband coding schemes using a regularized image restoration technique are proposed: the first controls the global regularity of the decompressed image; the second extends the first approach at each decomposition level. The quantization scheme incorporates scalar quantization (SQ) and pyramidal lattice vector quantization (VQ) with both optimal bit and quantizer allocation. Experimental results show that both the block effect due to VQ and the quantization noise are significantly reduced.     

The big squeeze-a CELP speech codec

The coding algorithm widely recognised as offering the best prospects for delivering toll-quality speech at very low bit rates is called CELP (codebook-excited linear prediction) coding. The CELP codec by Delphi Systems operates in real time, uses a standard digital signal processing chip, and encodes speech at 4.8 and 6.5 kbit/s. The use of this speech compression codec (SCC) is also discussed     

Rate-distortion-constrained subband video coding

This paper introduces a subband video coding algorithm for operation over a continuum of rates from very low to very high. The key elements of the system are statistical rate-distortion-constrained motion estimation and compensation, multistage residual quantization, high order statistical modeling, and arithmetic coding. The method is unique in that it provides an improved mechanism for dynamic spatial and temporal coding. Motion vectors are determined in a nontraditional way, using a rate-distortion cost criterion. This results in a smoother and more consistent motion field, relative to that produced by conventional block matching algorithms. Control over the system computational complexity and performance may be exercised easily     

Improving speech quality of CELP coder

Although the speech quality of the code excited linear prediction (CELP) coder at 4800 bit/s is relatively good, it is still perceived as rough or noisy. The authors propose a residual shaping method that produces, without signal distortion, quality comparable to that obtained by adaptive postfiltering. The proposed method is particularly effective in the multiple tandeming environment.<>     

Boundary filter optimization for segmentation-based subband coding

This paper presents boundary optimization techniques for the nonexpansive decomposition of arbitrary-length signals with multirate filterbanks. Both biorthogonal and paraunitary filterbanks are considered. The paper shows how matching moments and orthonormality can be imposed as additional conditions during the boundary filter optimization process. It provides direct solutions to the problem of finding good boundary filters for the following cases: (a) biorthogonal boundary filters with exactly matching moments and (b) orthonormal boundary filters with almost matching moments. With the proposed methods, numerical optimization is only needed if orthonormality and exactly matching moments are demanded. The proposed direct solutions are applicable to systems with a large number of subbands and/or very long filter impulse responses. Design examples show that the methods allow the design of boundary filters with good frequency selectivity     

Three-dimensional subband coding of video

We describe and show the results of video coding based on a three-dimensional (3-D) spatio-temporal subband decomposition. The results include a 1-Mbps coder based on a new adaptive differential pulse code modulation scheme (ADPCM) and adaptive bit allocation. This rate is useful for video storage on CD-ROM. Coding results are also shown for a 384-kbps rate that are based on ADPCM for the lowest frequency band and a new form of vector quantization (geometric vector quantization (GVQ)) for the data in the higher frequency bands. GVQ takes advantage of the inherent structure and sparseness of the data in the higher bands. Results are also shown for a 128-kbps coder that is based on an unbalanced tree-structured vector quantizer (UTSVQ) for the lowest frequency band and GVQ for the higher frequency bands. The results are competitive with traditional video coding techniques and provide the motivation for investigating the 3-D subband framework for different coding schemes and various applications.     

New directions in subband coding

Two very different subband coders are described. The first is a modified dynamic bit-allocation-subband coder (D-SBC) designed for variable rate coding situations and easily adaptable to noisy channel environments. It can operate at rates as low as 12 kb/s and still give good quality speech. The second coder is a 16-kb/s waveform coder, based on a combination of subband coding and vector quantization (VQ-SBC). The key feature of this coder is its short coding delay, which makes it suitable for real-time communication networks. The speech quality of both coders has been enhanced by adaptive postfiltering. The coders have been implemented on a single AT&T DSP32 signal processor     

Region adaptive subband image coding

We present a region adaptive subband image coding scheme using the statistical properties of image subbands for various subband decompositions. Motivated by analytical results obtained when the input signal to the subband decomposition is a unit step function, we analyze the energy packing properties toward the lower frequency subbands, edges, and the dependency of energy distribution on the orientation of the edges, in subband decomposed images. Based on these investigations and ideal analysis/synthesis filtering done in the frequency domain, the region adaptive subband image coding scheme extracts suitably shaped regions in each subband and then uses adaptive entropy-constrained quantizers for different regions under the assumption of a generalized Gaussian distribution for the image subbands. We also address the problem of determining an optimal subband decomposition among all possible decompositions. Experimental results show that visual degradations in the reconstructed image are negligible at a bit rate of 1.0 b/pel and reasonable quality images are obtainable at rates as low as 0.25 b/pel.     

Rate-distortion-optimal subband coding withoutperfect-reconstruction constraints

We investigate the design of subband coders without the traditional perfect-reconstruction constraint on the filters. The coder uses scalar quantizers, and its filters and bit allocation are designed to optimize a rate-distortion criterion. Using convexity analysis, we show that optimality can be achieved using filterbanks that are the cascade of a (paraunitary) principal component filterbank for the input spectral process and a set of pre and postfilters surrounding each quantizer. Analytical expressions for the pre and postfilters are then derived. An algorithm for computing the globally optimal filters and bit allocation is given. We also develop closed-form solutions for the special case of two-channel coders under an exponential rate-distortion model. Finally, we investigate a constrained-length version of the filter design problem, which is applicable to practical coding scenarios. While the optimal filterbanks are nearly perfect-reconstruction at high rates, we demonstrate an apparently surprising advantage of optimal FIR filterbanks; they significantly outperform optimal perfect-reconstruction FIR filterbanks at all bit rates     

Adaptive source-channel subband video coding for wireless channels

This paper presents a general framework for combined source-channel coding within the context of subband coding. The unequal importance of subbands in reconstruction of the source is exploited by an appropriate allocation of source and channel coding rates for the coding and transmission of subbands over a noisy channel. For each subband, the source coding rate as well as the level of protection (quantified by the channel coding rate) are jointly chosen to minimize the total end-to-end mean-squared distortion suffered by the source. This allocation of source and channel coding rates is posed as a constrained optimization problem, and solved using a generalized bit allocation algorithm. The optimal choice of source and channel coding rates depends on the state of the physical channel. These results are extended to transmission over fading channels using a finite state model, where every state corresponds to an additive white Gaussian noise (AWGN) channel. A coding strategy is also developed that minimizes the average distortion when the channel state is unavailable at the transmitter. Experimental results are provided that demonstrate application of these combined source-channel coding strategies on video sequences     

An integrated framework for adaptive subband image coding

Previous work on filter banks and related expansions has revealed an interesting insight: different filter bank trees can be regarded as different ways of constructing orthonormal bases for linear signal expansion. In particular, fast algorithms for finding best bases in an operational rate-distortion (R/D) sense have been successfully used in image coding. Independently of this work, other research has also explored the design of filter banks that optimize energy compaction for a single signal or a class of signals. In this paper, we integrate these two different but complementary approaches to best-basis design and propose a coding paradigm in which subband filters, tree structure, and quantizers are chosen to optimize the R/D performance. These coder attributes represent side information. They are selected from a codebook designed off-line from training data, using R/D as the design criterion. This approach provides a rational framework in which to explore alternatives to empirical design of filter banks, quantizers, and other coding parameters. The on-line coding algorithm is a relatively simple extension of current R/D-optimal coding algorithms that operate with fixed filter banks and empirically designed quantizer codebooks. In particular, it is shown that selection of the best adapted filter bank from the codebook is computationally elementary     

Minimum mean-squared error transform coding and subband coding

Knowledge of the power spectrum of a stationary random sequence can be used for quantizing the signal efficiently and with minimum mean-squared error. A multichannel filter is used to transform the random sequence into an intermediate set of variables that are quantized using independent scalar quantizers, and then inverse-filtered, producing a quantized version of the original sequence. Equal word-length and optimal word-length quantization at high bit rates is considered. An analytical solution for the filter that minimizes the mean-squared quantization error is obtained in terms of its singular value decomposition. The performance is characterized by a set of invariants termed second-order modes, which are derived from the eigenvalue decomposition of the matrix-valued power spectrum. A more general rank-reduced model is used for decreasing distortion by introducing bias. The results are specialized to the case when the vector-valued time series is obtained from a scalar random sequence, which gives rise to a filter bank model for quantization. The asymptotic performance of such a subband coder is derived and shown to coincide with the asymptotic bound for transform coding. Quantization employing a single scalar pre- and postfilter, traditional transform coding using a square linear transformation, and subband coding in filter banks, arise as special cases of the structure analyzed here