During the last decade, CD-quality digital audio has essentially replaced analog audio. Emerging digital audio applications for network, wireless, and multimedia computing systems face a series of constraints such as reduced channel bandwidth, limited storage capacity, and low cost. These new applications have created a demand for high-quality digital audio delivery at low bit rates. In response to this need, considerable research has been devoted to the development of algorithms for perceptually transparent coding of high-fidelity (CD-quality) digital audio. As a result, many algorithms have been proposed, and several have now become international and/or commercial product standards. This paper reviews algorithms for perceptually transparent coding of CD-quality digital audio, including both research and standardization activities. This paper is organized as follows. First, psychoacoustic principles are described, with the MPEG psychoacoustic signal analysis model 1 discussed in some detail. Next, filter bank design issues and algorithms are addressed, with a particular emphasis placed on the modified discrete cosine transform, a perfect reconstruction cosine-modulated filter bank that has become of central importance in perceptual audio coding. Then, we review methodologies that achieve perceptually transparent coding of FM- and CD-quality audio signals, including algorithms that manipulate transform components, subband signal decompositions, sinusoidal signal components, and linear prediction parameters, as well as hybrid algorithms that make use of more than one signal model. These discussions concentrate on architectures and applications of those techniques that utilize psychoacoustic models to exploit efficiently masking characteristics of the human receiver. Several algorithms that have become international and/or commercial standards receive in-depth treatment, including the ISO/IEC MPEG family (-1, -2, -4), the Lucent Technologies PAC/EPAC/MPAC, the Dolby AC-2/AC-3, and the Sony ATRAC/SDDS algorithms. Then, we describe subjective evaluation methodologies in some detail, including the ITU-R BS.1116 recommendation on subjective measurements of small impairments. This paper concludes with a discussion of future research directions.

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Perceptual coding of digital audio

An exact analysis of the critically subsampled two-band modelization scheme is given, and it is demonstrated that adaptive cross-filters between the subbands are necessary for modelization with small output errors. It is shown that perfect reconstruction filter banks can yield exact modelization. These results are extended to the critically subsampled multiband schemes, and important computational savings are seen to be achieved by using good quality filter banks. The problem of adaptive identification in critically subsampled subbands is considered and an appropriate adaptation algorithm is derived. The authors give a detailed analysis of the computational complexity of all the discussed schemes, and experimentally verify the theoretical results that are obtained. The adaptive behavior of the subband schemes that were tested is discussed. >

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Adaptive filtering in subbands with critical sampling: analysis, experiments, and application to acoustic echo cancellation

Adaptive filtering in subbands is a new technique for the real-time identification of large impulse responses like the ones encountered in acoustic echo cancellation. This tech- nique generally allows computational savings as well as better convergence behavior. We give first an exact analysis of the critically subsampled two band modelization scheme. We demonstrate that adaptive cross-filters between the subbands are necessary for modeliza- tion with small output errors; moreover, we show that perfect reconstruction filter banks can yield exact modelization. We ex- tend those results to the critically subsampled multiband schemes, and we show that important computational savings can be achieved by using good quality filter banks. Then we consider the problem of adaptive identification in critically sub- sampled subbands, and we derive an appropriate adaptation algorithm. We give a detailed analysis of the computational complexity of all the discussed schemes, and we verify experi- mentally the theoretical results that we have obtained. Finally, we discuss the adaptive behavior of the subband schemes that we have tested. We generally observe some degradation of the convergence performance in comparison with conventional schemes; however, the overall performance could be acceptable in practical use.

Adaptive Filtering in Subbands with Critical Sampling: Analysis, Experiments, and Application to Acoustic

Multirate filter banks produce multiple output signals by filtering and subsampling a single input signal, or conversely, generate a single output by upsampling and interpolating multiple inputs. Two of their main applications are subband coders for speech processing and transmultiplexers for telecommunications. Below, we derive a theoretical framework for the analysis, synthesis, and computational complexity of multirate filter banks. The use of matrix notation leads to basic results derived from properties of linear algebra. Using rank and determinant of filter matrices, it is shown how to obtain aliasing/ crosstalk-free reconstruction, and when perfect reconstruction is possible. The synthesis of filters for filter banks is also explored, three design methods are presented, and finally, the computational complexity is considered.

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A theory of multirate filter banks

The authors obtain a necessary and sufficient condition on the 2M (M=number of channels) polyphase components of a linear-phase prototype filter of length N=2 mM (where m=an arbitrary positive integer), such that the polyphase component matrix of the modulated filter is lossless. The losslessness of the polyphase component matrix, in turn, is sufficient to ensure that the analysis/synthesis system satisfies perfect reconstruction (PR). Using this result, a novel design procedure is presented based on the two-channel lossless lattice. This enables the design of a large class of FIR (finite impulse response)-PR filter banks, and includes the N=2M case. It is shown that this approach requires fewer parameters to be optimized than in the pseudo-QMF (quadrature mirror filter) designs and in the lossless lattice based PR-QMF designs (for equal length filters in the three designs). This advantage becomes significant when designing long filters for large M. The design procedure and its other advantages are described in detail. Design examples and comparisons are included. >

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Cosine-modulated FIR filter banks satisfying perfect reconstruction

This paper introduces a flexible design method of computationally efficient uniform filter bank where each filter channel is obtained by frequency translation of a prototype base-band filter. It is shown that the original signal decomposed by the analysis filter bank into N adjacent uniform subbands subsampled by N, can be reconstructed with negligible distortion. We give a practical implementation which allows an important reduction in computational complexity. It can be therefore applied to such signal processing tasks as speech coding or spectral parametrization of signals.

J. Masson

Papers

Flexible design of computationaly efficient nearly perfect QMF filter banks