The 3GPP IVAS codec specifies an EVS-compatible stereo downmix as one of the key functionalities. This paper describes how this novel active downmix scheme has been devised to achieve high and stable quality from stereo input to EVS encoder/decoder with no additional algorithmic delay. An example of a network configuration for a multi-party conference using the proposed EVS-compatible downmix is also provided. This paper shows several fundamental schemes, of active processes, including adaptive weight and phase-compensated weight between two channels. Subjective listening test results show that the devised scheme’s quality is better than that of a passive downmix.

We present an efficient construction of variable-to-fixed-length (VF) codes under conditions where encoding delay is allowed. We introduce a generalized form of parsetree sets representing a class of codes broader than the almost instantaneous VF (AIVF) codes, which are the conventional VF codes that allow one symbol of an encoding delay. Using Huffman trees, we can optimally construct the codes and guarantee that the compression efficiency is at least compatible with Huffman codes. Numerical evaluations show that we can make efficient VF codes that outperform Huffman codes even for input sources that are disadvantageous to conventional VF codes.

This paper presents an optimal construction ofN-bit-delay almost instantaneous fixed-to-variable-length (AIFV) codes, the general form of binary codes we can make when finite bits of decoding delay are allowed. The presented method enables us to optimize lossless codes among a broader class of codes compared to the conventional FV and AIFV codes. The paper first discusses the problem of code construction, which contains some essential partial problems, and defines three classes of optimality to clarify how far we can solve the problems. The properties of the optimal codes are analyzed theoretically, showing the sufficient conditions for achieving the optimum. Then, we propose an algorithm for constructingN-bit-delay AIFV codes for given stationary memory-less sources. The optimality of the constructed codes is discussed both theoretically and empirically. They showed shorter expected code lengths whenN≥ 3 than the conventional AIFV-mand extended Huffman codes. Moreover, in the random numbers simulation, they performed higher compression efficiency than the 32-bit-precision range codes under reasonable conditions.

A general class of the almost instantaneous fixed-to-variable-length (AIFV) codes is proposed, which contains every possible binary code we can make when allowing finite bits of decoding delay. The contribution of the paper lies in the following. (i) Introducing$N$-bit-delay AIFV codes, constructed by multiple code trees with higher flexibility than the conventional AIFV codes. (ii) Proving that the proposed codes can represent any uniquely-encodable and uniquely-decodable variable-to-variable length codes. (iii) Showing how to express codes as multiple code trees with minimum decoding delay. (iv) Formulating the constraints of decodability as the comparison of intervals in the real number line. The theoretical results in this paper are expected to be useful for further study on AIFV codes.

Entropy coding, which is an essential part of audio compression, is always required to manage the tradeoffs between compression efficiency and computational complexity, and the strategy to achieve them highly depends on the distributions of inputs. In this paper, we present a method of controlling them for enhancing the compression efficiency of Golomb-Rice (GR) encoding, one of the simplest entropy coding methods optimal for Laplacian distributions. We will show that the proposed invertible and low-complexity mapping of integers enables the GR encoding to assign nearly the optimal code length for a wider range of distributions, generalized Gaussian distributions, maintaining low computational cost. A simulation by random numbers reveals that the proposed coder based on this scheme works about 6 times faster than the state-of-the-art arithmetic coder for Gaussian-distributed integers maintaining the increase in relative redundancy around 2.6%, which is much lower than that of a conventional GR coder. Additionally, an application to a practical speech and audio coding scheme is presented, and an objective evaluation for real speech and audio signals confirms the advantages of the proposed method in compression. The method is expected to widen the capability of low-complexity entropy coding, providing us with more flexible codec designs.

This paper presents a qualitative approach of combining Golomb-Rice (GR) code with algebraic bijective mappings which losslessly convert between arbitrary positive integers of different dimension and shape the distribution of generalized Gaussian sources. The mappings, integer nesting and splitting, enables GR encoding, with a little additional computation, to compress more efficiently sources based on wider classes of distributions than Laplacian. Simulations showed, especially for some Gaussian sources, almost optimal average code length can be achievable by performing integer nesting before GR encoding the integers. This scheme will be useful for applications dealing with various types of sources and requiring low computational costs.

We have devised a method for bit assignment of quantized frequency spectra aiming at its use in low-delay bit-error-robust speech compression. The proposed method, least significant bit management (LSBM), controls the least significant bits of the spectra based on their envelope to make them represented by fixed bit rates, which guarantees the range of the damage caused by the bit error which makes the mismatch of the spectral envelopes between the encoder and the decoder. In addition, we relate the method to the linear predictive coding scheme and show its performance and robustness in a speech codec by objective and subjective evaluations. The codec based on this method, having bit-error robustness with only 1.5-ms algorithmic delay, can be useful at such situations as real-time speech communication with non-IP protocols.

This paper presents an extension of GolombRice (GR) code for coding low-entropy sources, which the gap between their entropy and the conventional GR code length gets larger. We mention here the following four facts related to the proposed code, extended-domain GR (XDGR) code: it is represented by multiple code trees, based on the idea of almost instantaneous fixed-to-variable length codes, with its algorithm being a generalization of unary coding; its structure naturally contains run-length coding; the gap between the entropy and its average code length is theoretically guaranteed to be asymptotically negligible as the entropy of the exponentially distributed sources tends to zero; and its coding parameter, corresponding to the negative-domain Rice parameter of GR code, can be estimated from the input source-symbol sequence. Experimental evaluations are also presented supporting the theorems. The proposed XDGR code, having simple algorithm and high compression performance, is expected to be used for many coding applications, which deals with exponentially distributed sources at low bit rates.

We have devised a method for estimating, from a single frame of audio frequency spectra, a shape parameter of multivariate generalized Gaussian distribution which has variance represented by an all-pole model and no covariance. Based on powered all-pole spectrum estimation (PAPSE), which is an extension of linear prediction, the proposed method simultaneously estimates the shape parameter and the maximum-likelihood variance, allowing more accurate representation of the probability density functions of the spectra. This paper shows an integration of the estimation into an audio codec for an example of its application, which resulted in the enhancement of the objective and subjective reconstruction quality. Since this estimation method provides us with simple parameters which reflect some acoustic features of signals, the method may also be useful in other audio signal processing problems.

We have devised a high-quality frequency-domain audio coder based on the state-of-the-art monaural wide-band coder aiming at its use in low-delay and low-bit-rate conditions. The coder efficiently represents frequency spectral envelopes of the target signals with low computational complexity using optimally prepared non-negative sparse matrices. The experimental results reveal that this representation has positive effects on the objective and subjective quality of the coder resulting in the comparable quality to the same bit rate of 3GPP Extended Adaptive Multi-Rate WideBand ( AMR-WB+), a coder which permits more than four times longer delay compared with the proposed coder. Consequently, this coder is suitable for applications in mobile communications, which require low delay and low complexity.

We present an optimal coding scheme that parameterizes the maximum-likelihood estimate of variance for frequency spectra belonging to the generalized Gaussian distribution, the distribution covering the Laplacian and the Gaussian. By slightly modifying the all-pole model of the conventional linear prediction (LP), we can estimate the variance with the same method as in LP, which has low computational costs. Experimental results show that incorporating the coding scheme in a state-of-the-art wide-band audio coder enhances its objective and subjective quality in a low-bit-rate and low-delay situation by increasing the compression efficiency. Thus, this coding scheme will be useful in applications like mobile communications, which requires highly efficient compression.