Abstract
With the increasing demand for high quality audio, stereo audio coding has become more and more important. In this paper, a multi-frame coding method based on Principal Component Analysis (PCA) is proposed for the compression of audio signals, including both mono and stereo signals. The PCA-based method makes the input audio spectral coefficients into eigenvectors of covariance matrices and reduces coding bitrate by grouping such eigenvectors into fewer number of vectors. The multi-frame joint technique makes the PCA-based method more efficient and feasible. This paper also proposes a quantization method that utilizes Pyramid Vector Quantization (PVQ) to quantize the PCA matrices proposed in this paper with few bits. Parametric coding algorithms are also employed with PCA to ensure the high efficiency of the proposed audio codec. Subjective listening tests with Multiple Stimuli with Hidden Reference and Anchor (MUSHRA) have shown that the proposed PCA-based coding method is efficient at processing stereo audio.
Highlights
The goal of audio coding is to represent audio in digital form with as few bits as possible while maintaining the intelligibility and quality required for particular applications [1]
It is very important to deal with the stereo signal efficiently, which can offer better experiences of using applications like mobile communication and live audio broadcasting
Intensity stereo is supported by many audio compression formats such as Advanced Audio Coding (AAC) [5,6], which is used for the transfer of relatively low bit rate, acceptable-quality audio with modest internet access speed
Summary
The goal of audio coding is to represent audio in digital form with as few bits as possible while maintaining the intelligibility and quality required for particular applications [1]. It is very important to deal with the stereo signal efficiently, which can offer better experiences of using applications like mobile communication and live audio broadcasting. Over these years, a variety of techniques for stereo signal processing have been proposed [2,3], including M/S stereo, intensity stereo, joint stereo, and parametric stereo. Intensity stereo works on the principle of sound localization [4]: humans have a less keen sense of perceiving the direction of certain audio frequencies By exploiting this characteristic, intensity stereo coding can reduce the bitrate with little or no perceived change in apparent quality. The idea behind parametric stereo coding is to maximize the compression of a stereo signal by transmitting parameters describing the spatial image
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