This paper proposes a blind digital audio water- marking algorithm that utilizes the quantization index modulation (QIM) and the singular value decomposition (SVD) of stereo audio signals. Conventional SVD-based blind audio watermarking algorithms lack physical interpretation since the matrix construction method for the input matrix for SVD is heuristically defined. However, in the proposed approach, because the SVD is directly applied to the stereo input signals, the resulting decomposed elements convey a conceptually meaningful inter- pretation of the original audio signal. As the proposed approach effectively utilizes the ratio of singular values, the embedded watermark is highly imperceptible and robust against volumetric scaling attacks; most QIM-based watermarking schemes are weak to these types of attacks. Experimental results under well-known practical attacks, such as compressions, resampling, and various types of signal processing, confirm that the proposed algorithm performs well compared to conventional audio watermarking algorithms.

This paper presents a multichannel dereverberation algorithm that only uses coherent acoustic channels. In the framework of multi-input/output inverse theorem (MINT), the equalization performance varies depending on the length of the input acoustic channels. However, only the portion of observed channel that resemble the true acoustic channel contributes to performance enhancement when measurement error is accounted. Hence, the proposed algorithm derives the frequency dependent viable channel length (VCL) from the coherence analysis of Monte Carlo observations of a single acoustic channel. The VCL of the room impulse response (RIR) is determined by the portion where the stochastic characteristic of multiple observations is highly coherent. Experiments are conducted to compare the equalization performance of the subband MINT algorithm depending on the length of the input RIR. The equalization performance using frequency dependent VCL is as good as the one obtained using the maximum length of the measured channel, while its complexity is significantly reduced.