Multi-channel Audio Compression Method Based on ITU-T G.719 Codec

Jiang, Wenjin; Wang, Jing; Zhao, Yi; Liu, Baoguang; Ji, Xuan

doi:10.1109/iih-msp.2013.81

Cited by 3 publications

(2 citation statements)

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“…The rate of transmission of the first principal component is around 10 kbps, so the parameter rate of PCA-based parametric stereo is around 15 kbps. In traditional parametric stereo [24], IPD of each subband is quantized by 3 bits, so the parameter rate of the traditional parameter stereo is about (4 + 3 + 3 + 3) × 25 × 50 = 16.25 kbps. Therefore, compared with traditional parametric stereo, the rate of PCA-based parametric stereo is slightly reduced.…”

Section: Subbands and Bitratementioning

confidence: 99%

“…(ii) Contrast test objects: PCA-based codec signal that transmits two channels separately, PCA-based codec signal with traditional parametric stereo, PCA-based codec signal with improved parametric stereo, G719 codec signal with traditional parametric stereo [24], HE-AACv2 codec signal, anchor signal, and original signal. In the algorithm proposed in this paper, the relationship between the quality of the restored signal and bitrate is not linear, as Figure 17 shows, which uses a simple subjective test with different bitrate allocation; therefore, the test chooses a case in which the qualities of restored signal and bitrate are both acceptable.…”

Section: Design Of Test Based On Mushramentioning

confidence: 99%

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A Multi-Frame PCA-Based Stereo Audio Coding Method

et al. 2018

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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.

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Section: Subbands and Bitratementioning

confidence: 99%

Section: Design Of Test Based On Mushramentioning

confidence: 99%