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Reconfigurable Multitask Audio Dynamics Processing Scheme

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Citation Author(s):
Jun Yang, Amit S. Chhetri, Carlo Murgia, Philip Hilmes
Submitted by:
Jun Yang
Last updated:
7 May 2019 - 4:47pm
Document Type:
Poster
Document Year:
2019
Event:
Presenters Name:
Jun Yang
Paper Code:
IDSP-P1.3

Abstract 

Abstract: 

Automatic speech recognition (ASR), audio quality, and loudness are key performance indicators (KPIs) in smart speakers. To improve all these KPIs, audio dynamics processing is a crucial component in related systems. Unfortunately, single-band and existing multiband dynamics processing (MBDP) schemes fail to maximize bass and loudness but even produce unwanted peaks, distortions, and nonlinear echo so that an optimized ASR performance cannot be achieved. It has been a goal in both industry and academia to find a better audio dynamics processing for mitigating these problems. To provide such a desired solution, this paper proposes a novel reconfigurable multitask MBDP scheme through a global optimization framework. Through extensive testing, we show the accuracy and effectiveness of the proposed scheme in terms of bass and loudness maximization, distortion and nonlinear echo reduction, browning-out prevention, and significant ASR performance improvement.

Full-length paper: https://ieeexplore.ieee.org/document/8682537

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Dataset Files

MBDP_ICASSP2019.pdf

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