AES New York 2007
Signal Processing, Part 1
Paper Session P2
Friday, October 5, 9:00 am — 11:00 am
Chair: Duane Wise, Consultant - Boulder, CO, USA
P2-1 Suppression of Musical Noise Artifacts in Audio Noise Reduction by Adaptive 2-D Filtering—Alexey Lukin, Moscow State University - Moscow, Russia; Jeremy Todd, iZotope, Inc. - Cambridge, MA, USA
Spectral attenuation algorithms for audio noise reduction often generate annoying musical noise artifacts. Most existing methods for suppression of musical noise employ a combination of instantaneous and time-smoothed spectral estimates for calculation of spectral gains. In this paper a 2-D approach to the filtering of a time-frequency spectrum is proposed, based on a recently developed non-local means image denoising algorithm. The proposed algorithm demonstrates efficient reduction of musical noise without creating “noise echoes” inherent in time-smoothing methods.
Convention Paper 7168 (Purchase now)
P2-2 Perceptually Motivated Gain Filter Smoothing for Noise Suppression—Alexis Favrot, Christof Faller, Illusonic LLC - Chavannes, Switzerland
Stationary noise suppression is widely used, mostly for reducing noise in speech signals or for audio restoration. Most noise suppression algorithms are based on spectral modification, i.e., a real-valued gain filter is applied to short-time spectra of the speech signal to reduce noise. The more noise is to be removed, the more likely are artifacts due to aliasing effects and time variance of the gain filter. A perceptually motivated systematic time and frequency smoothing of the gain filter is proposed to improve quality, considering the frequency resolution of the auditory system and masking. Comparison with a number of previous methods indicates that the proposed noise suppressor performs as good as the best other method, while computational complexity is much lower.
Convention Paper 7169 (Purchase now)
P2-3 A Novel Automatic Noise Removal Technique for Audio and Speech Signals—Harinarayanan E.V., ATC Labs - Noida, India; Deepen Sinha, ATC Labs - Chatham, NJ, USA; Shamail Saeed, ATC Labs - Noida, India; Anibal Ferreira, University of Porto - Porto, Portugal, and ATC Labs, Chatham, NJ, USA
This paper introduces new ideas on wideband stationary/nonstationary noise removal for audio signals. Current noise reduction techniques have generally proven to be effective, yet these typically exhibit certain undesirable characteristics. Distortion and/or alteration of the audio characteristics of primary audio sound is a common problem. Also user intervention in identifying the noise profile is sometimes necessary. The proposed technique is centered on the classical Kalman filtering technique for noise removal but uses a novel architecture whereby advanced signal processing techniques are used to identify and preserve the richness of the audio spectrum. The paper also includes conceptual and derivative results on parameter estimation, a description of multi-parameter Signal Activity Detector (SAD), and our new-found improved results.
Convention Paper 7170 (Purchase now)
P2-4 The Concept, Design, and Implementation of a General Dynamic Parametric Equalizer—Duane Wise, Wholegrain Digital Systems, LLC - Boulder, CO, USA
The classic operations of dynamics processing and parametric equalization control two separate domains of an audio signal. The operational nature of the two processors give insight to a manner in which they may be combined into a single processor. This integrated processor can perform as the equivalent of a standalone dynamics processor or parametric equalizer, but can also modify the boost and/or cut of an equalizer stage over time following a dynamics curve. The design of a digital version of this concept is discussed herein, along with implementation issues and proposals for their resolutions.
Convention Paper 7171 (Purchase now)
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