基于模型的动态范围压缩反演

IEEE Transactions on Audio Speech and Language Processing Pub Date : 2013-07-01 DOI:10.1109/TASL.2013.2253099

Stanislaw Gorlow, J. Reiss

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引用次数: 24

摘要

在这项工作中，它显示了如何动态非线性时变算子，如动态范围压缩器，可以使用显式信号模型进行反转。通过了解用于压缩的模型参数，可以从“广播”信号中恢复原始未压缩信号，具有很高的数值精度和非常低的计算复杂度。提出了一种压缩-减压方案，并对其进行了详细描述。该方法在实际音频材料上进行了测试，取得了很大的成功。

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Model-Based Inversion of Dynamic Range Compression

In this work it is shown how a dynamic nonlinear time-variant operator, such as a dynamic range compressor, can be inverted using an explicit signal model. By knowing the model parameters that were used for compression one is able to recover the original uncompressed signal from a “broadcast” signal with high numerical accuracy and very low computational complexity. A compressor-decompressor scheme is worked out and described in detail. The approach is evaluated on real-world audio material with great success.

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来源期刊

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

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.