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2018
Conference Paper
Titel
Improved psychoacoustic model for efficient perceptual audio codecs
Abstract
Since early perceptual audio coders such as mp3, the underlying psychoacoustic model that controls the encoding process has not undergone many dramatic changes. Meanwhile, modern audio coders have been equipped with semi-parametric or parametric coding tools such as audio bandwidth extension. Thereby, the initial psychoacoustic model used in a perceptual coder, just considering added quantization noise, became partly unsuitable. We propose the use of an improved psychoacoustic excitation model based on an existing model proposed by Dau et al. in 1997. This modulation-based model is essentially independent from the input waveform by calculating an internal auditory representation. Using the example of MPEG-H 3D Audio and its semi-parametric Intelligent Gap Filling (IGF) tool, we demonstrate that we can successfully control the IGF parameter selection process to achieve overall improved perceptual quality.