XAttnMark is a new neural audio watermarking method using partial parameter sharing, cross-attention for message retrieval, temporal conditioning, and a psychoacoustic TF masking loss that reports state-of-the-art detection and attribution robustness.
Robust Audio Watermarking Algorithm Based on Moving Average and DCT
1 Pith paper cite this work. Polarity classification is still indexing.
1
Pith paper citing it
abstract
Noise is often brought to host audio by common signal processing operation, and it usually changes the high-frequency component of an audio signal. So embedding watermark by adjusting low-frequency coefficient can improve the robustness of a watermark scheme. Moving Average sequence is a low-frequency feature of an audio signal. This work proposed a method which embedding watermark into the maximal coefficient in discrete cosine transform domain of a moving average sequence. Subjective and objective tests reveal that the proposed watermarking scheme maintains highly audio quality, and simultaneously, the algorithm is highly robust to common digital signal processing operations, including additive noise, sampling rate change, bit resolution transformation, MP3 compression, and random cropping, especially low-pass filtering.
fields
cs.SD 1years
2025 1verdicts
UNVERDICTED 1representative citing papers
citing papers explorer
-
XAttnMark: Learning Robust Audio Watermarking with Cross-Attention
XAttnMark is a new neural audio watermarking method using partial parameter sharing, cross-attention for message retrieval, temporal conditioning, and a psychoacoustic TF masking loss that reports state-of-the-art detection and attribution robustness.