About: TwinVQ is a research topic. Over the lifetime, 23 publications have been published within this topic receiving 282 citations. The topic is also known as: VQF.
TL;DR: A new audio-coding method is proposed, called transform-domain weighted interleave vector quantization (TwinVQ), which achieves high-quality reproduction at less than 64 kbit/s and exceeded that of an MPEG Layer II coder at the same bitrate.
Abstract: A new audio-coding method is proposed. This method is called transform-domain weighted interleave vector quantization (TwinVQ) and achieves high-quality reproduction at less than 64 kbit/s. The method is a transform coding using modified discrete cosine transform (MDCT). There are three novel techniques in this method: flattening of the MDCT coefficients by the spectrum of linear predictive coding (LPC) coefficients; interframe backward prediction for flattening the MDCT coefficients; and weighted interleave vector quantization. Subjective evaluation tests showed that the quality of the reproduction of TwinVQ exceeded that of an MPEG Layer II coder at the same bitrate.
TL;DR: This paper proposes two novel techniques for twinVQ (transform domain weighted interleave VQ) high-quality audio coding scheme for rates lower than 64 kbit/s by means of a interpolated square root LPC (linear predictive coding) spectrum.
Abstract: This paper proposes two novel techniques for twinVQ (transform domain weighted interleave VQ) high-quality audio coding scheme for rates lower than 64 kbit/s. One is an extension of the weighted interleave technique to the time and input channel domains as well as the frequency domain. The other is an efficient representation scheme of the spectral envelope by means of a interpolated square root LPC (linear predictive coding) spectrum.
TL;DR: The energy equalization quality metric (EEQM) is described for predicting the relative perceptual performance of the different coding algorithms and its predictive ability is compared with that of ITU Recommendation ITU-R BS.
Abstract: In this paper, we study coding artifacts in MPEG-compressed scalable audio. Specifically, we consider the MPEG advanced audio coder (AAC) using bit slice scalable arithmetic coding (BSAC) as implemented in the MPEG-4 reference software. First we perform human subjective testing using the comparison category rating (CCR) approach, quantitatively comparing the performance of scalable BSAC with the nonscaled TwinVQ and AAC algorithms. This testing indicates that scalable BSAC performs very poorly relative to TwinVQ at the lowest bitrate considered (16 kb/s) largely because of an annoying and seemingly random mid-range tonal signal that is superimposed onto the desired output. In order to better understand and quantify the distortion introduced into compressed audio at low bit rates, we apply two analysis techniques: Reng bifrequency probing and time-frequency decomposition. Using Reng probing, we conclude that aliasing is most likely not the cause of the annoying tonal signal; instead, time-frequency or spectrogram analysis indicates that its cause is most likely suboptimal bit allocation. Finally, we describe the energy equalization quality metric (EEQM) for predicting the relative perceptual performance of the different coding algorithms and compare its predictive ability with that of ITU Recommendation ITU-R BS.1387-1.