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Appl. Sci. 2018, 8(1), 96; https://doi.org/10.3390/app8010096

Audlet Filter Banks: A Versatile Analysis/Synthesis Framework Using Auditory Frequency Scales

1
Acoustics Research Institute, Austrian Academy of Sciences, Wohllebengasse 12–14, 1040 Vienna, Austria
2
Universite de Toulon, Aix-Marseille Universite, CNRS-PRISM, 31 Chemin Joseph Aiguier, 13402 Marseille CEDEX 20, France
*
Author to whom correspondence should be addressed.
Academic Editor: Vesa Valimaki
Received: 3 November 2017 / Revised: 15 December 2017 / Accepted: 3 January 2018 / Published: 11 January 2018
(This article belongs to the Special Issue Sound and Music Computing)
Full-Text   |   PDF [586 KB, uploaded 11 January 2018]   |  

Abstract

Many audio applications rely on filter banks (FBs) to analyze, process, and re-synthesize sounds. For these applications, an important property of the analysis–synthesis system is the reconstruction error; it has to be minimized to avoid audible artifacts. Other advantageous properties include stability and low redundancy. To exploit some aspects of auditory perception in the signal chain, some applications rely on FBs that approximate the frequency analysis performed in the auditory periphery, the gammatone FB being a popular example. However, current gammatone FBs only allow partial reconstruction and stability at high redundancies. In this article, we construct an analysis–synthesis system for audio applications. The proposed system, referred to as Audlet, is an oversampled FB with filters distributed on auditory frequency scales. It allows perfect reconstruction for a wide range of FB settings (e.g., the shape and density of filters), efficient FB design, and adaptable redundancy. In particular, we show how to construct a gammatone FB with perfect reconstruction. Experiments demonstrate performance improvements of the proposed gammatone FB when compared to current gammatone FBs in terms of reconstruction error and stability, especially at low redundancies. An application of the framework to audio source separation illustrates its utility for audio processing. View Full-Text
Keywords: audio signal processing; analysis–synthesis; filter bank; time-frequency transform; frames; hearing; gammatone; equivalent rectangular bandwidth (ERB); Bark scale; Mel scale audio signal processing; analysis–synthesis; filter bank; time-frequency transform; frames; hearing; gammatone; equivalent rectangular bandwidth (ERB); Bark scale; Mel scale
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This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited (CC BY 4.0).

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Necciari, T.; Holighaus, N.; Balazs, P.; Průša, Z.; Majdak, P.; Derrien, O. Audlet Filter Banks: A Versatile Analysis/Synthesis Framework Using Auditory Frequency Scales. Appl. Sci. 2018, 8, 96.

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