Modern transform audio coders often employ parametric enhancements, like noise substitution or bandwidth extension. In addition to these well-known parametric tools, it might also be desirable to synthesize parametric...
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ISBN:
(纸本)9781479903566
Modern transform audio coders often employ parametric enhancements, like noise substitution or bandwidth extension. In addition to these well-known parametric tools, it might also be desirable to synthesize parametric sinusoidal tones in the decoder. Low computational complexity is an important criterion in codec development and essential for acceptance and deployment. Therefore, efficient ways of generating these tones are needed. Since contemporary codecs like AAC or USAC are based on an MDCT domain representation of audio, we propose to generate synthetic tones by patching tone patterns into the MDCT spectrum at the decoder. We demonstrate how appropriate spectral patterns can be derived and adapted to their target location in (and between) the MDCT time/frequency (t/f) grid to seamlessly synthesize high quality sinusoidal tones including sweeps.
This work is concerned with the development and optimization of a signal model for scalable perceptual audiocoding at low bit rates. A complementary two-part signal model consisting of Sines plus Noise (SN) is descri...
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This work is concerned with the development and optimization of a signal model for scalable perceptual audiocoding at low bit rates. A complementary two-part signal model consisting of Sines plus Noise (SN) is described. The paper presents essentially a fundamental enhancement to the sinusoidal modeling component. The enhancement involves an audio signal scheme based on carrying out overlap-add sinusoidal modeling at three successive time scales, large, medium, and small. The sinusoidal modeling is done in an analysis-by-synthesis overlap- add manner across the three scales by using a psychoacoustically weighted matching pursuits. The sinusoidal modeling residual at the first scale is passed to the smaller scales to allow for the modeling of various signal features at appropriate *** approach greatly helps to correct the pre-echo inherent in the sinusoidal model. This improves the perceptual audio quality upon our previous work of sinusoidal modeling while using tile same number of sinusoids. Tile most obvious application for the SN model is in scalable, high fidelity audiocoding and signal modification.
Sinusoidal models are widely used in parametric speech and audiocoding schemes. A common requirement in these applications is to select only a subset of components that provide the greatest perceptual benefit particu...
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ISBN:
(纸本)9781479903573
Sinusoidal models are widely used in parametric speech and audiocoding schemes. A common requirement in these applications is to select only a subset of components that provide the greatest perceptual benefit particularly at low bit-rates. Usually, perceptual sinusoidal component selection algorithms make use of greedy algorithms that are computationally expensive. In this paper, we present a new algorithm that selects sinusoidal components based on the partial loudness model proposed by Moore & Glasberg. We compare the performance of the proposed algorithm in terms of perceptual benefit and computational complexity to other existing sinusoidal selection algorithms.
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