Compensation of Loudspeaker–Room Responses in a Robust MIMO Control Framework

Lars-Johan Brännmark, A. Bahne, A. Ahlén
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引用次数: 25

Abstract

A new multichannel approach to robust broadband loudspeaker-room equalization is presented. Traditionally, the equalization (or room correction) problem has been treated primarily by single-channel methods, where loudspeaker input signals are prefiltered individually by separate scalar filters. Single-channel methods are generally able to improve the average spectral flatness of the acoustic transfer functions in a listening region, but they cannot reduce the variability of the transfer functions within the region. Most modern audio reproduction systems, however, contain two or more loudspeakers, and in this paper we aim at improving the equalization performance by using all available loudspeakers jointly. To this end we propose a polynomial based MIMO formulation of the equalization problem. The new approach, which is a generalization of an earlier single-channel approach by the authors, is found to reduce the average reproduction error and the transfer function variability over a region in space. Moreover, pre-ringing artifacts are avoided, and the reproduction error below 1000 Hz is significantly reduced with an amount that scales with the number of loudspeakers used.
鲁棒MIMO控制框架下扬声器-房间响应补偿
提出了一种新的多通道宽带扩音室鲁棒均衡方法。传统上,均衡(或房间校正)问题主要通过单通道方法处理,其中扬声器输入信号由单独的标量滤波器单独预滤波。单通道方法一般能够提高聆听区域内声学传递函数的平均频谱平坦度,但不能降低该区域内传递函数的可变性。然而,大多数现代音频重放系统包含两个或多个扬声器,在本文中,我们旨在通过联合使用所有可用的扬声器来提高均衡性能。为此,我们提出了一种基于多项式的MIMO均衡问题公式。新方法是作者早期的单通道方法的推广,发现可以减少空间区域内的平均再现误差和传递函数变异性。此外,避免了预振铃伪影,并且随着所使用的扬声器数量的增加,显着降低了低于1000 Hz的再现误差。
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来源期刊
IEEE Transactions on Audio Speech and Language Processing
IEEE Transactions on Audio Speech and Language Processing 工程技术-工程:电子与电气
自引率
0.00%
发文量
0
审稿时长
24.0 months
期刊介绍: The IEEE Transactions on Audio, Speech and Language Processing covers the sciences, technologies and applications relating to the analysis, coding, enhancement, recognition and synthesis of audio, music, speech and language. In particular, audio processing also covers auditory modeling, acoustic modeling and source separation. Speech processing also covers speech production and perception, adaptation, lexical modeling and speaker recognition. Language processing also covers spoken language understanding, translation, summarization, mining, general language modeling, as well as spoken dialog systems.
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