Abstract: A system, method, and computer program product are provided for artifact reduction in high-frequency regeneration audio signals. In operation, a high-frequency regeneration (HFR) audio signal is received. Additionally, one or more artifacts are detected in the received HFR audio signal, utilizing a spectral energy associated with the received HFR audio signal. Further, the received HFR audio signal is modified to at least partially correct the one or more artifacts in the received HFR audio signal.

Abstract: A high degree of compression can be achieved in audio and image coding systems by using a multiple-stage lossless encoding process having low computational cost that does not require high-accuracy pre-defined probability distribution functions of the information to be compressed. The multiple-stage encoding process classifies the signal components to be compressed into one of several classifications according to signal component value. Signal components placed into higher-level classifications are represented by tokens in the lower-level classifications. Each stage of the encoding process forms groups of signal components and tokens and applies a multi-dimensional encoding process to the groups. The dimension of the coding process is equal to the size of the group to which it is applied, and is chosen to balance computational requirements of the encoding process against compression performance.

Abstract: Many perceptual split-band coding systems that use analysis and synthesis filters assume the quantization noise introduced by quantizing split-band signals is substantially the same as the noise that results in the output signal obtained by applying the synthesis filters to the quantized split-band signals. In general, this assumption is not true because the synthesis filters modify or spread the quantization noise. A theoretical framework for deriving an optimum bit allocation that accounts for synthesis-filter noise spreading is disclosed. In concept, the problem of finding an optimal bit allocation can be expressed as a linear optimization problem in a multidimensional coordinate space. Simplified processes derived from this theoretical framework are disclosed that can obtain near-optimal solutions using modest computational resources.

Abstract: A method of digitally compressing speech and music by use of multiple band ("multiband") fixed excitations stored in codebooks. The use of multiband fixed excitations, along with a coupling method for interconnecting the excitation codebooks and adaptive codebooks and for generating the composite excitation signal, improve the long-term and short-term prediction, and the use of voice-music classification allows the coding structure to be adapted to the statistical character of the audio signal.