In this paper, we propose a robust audio watermarking technique which adopts the wavelet QIM method with adaptive step sizes for blind watermark extraction. Since wavelet transform offers both temporal and frequency resolutions, it is suitable for audio signal processing. The original audio signal is first segmented and divided into 29 subbands via wavelet packet decomposition. The bandwidth allocation of the subband decomposition structure is close to the critical band structure of human auditory system. According to Psychoacoustic Model, middle-low subbands are chosen for watermark embedding.

The adaptive step size technique is applied to audio signals with different characteristics based on the criterion that SNR must be maintained above 20 dB so that it is robust and transparent. We formulate the step size of each frame to be proportional to the magnitude of the audio signal. No side information on the step sizes need to be transmitted.

We analyze the performance of the proposed algorithms in terms of data SNR and Normalized Correlation (NC). The experimental results show that the embedding capacity is around 4 bits/frame and the watermark is robust against MP3 compression at 64 Kbps, resampling, requantization, and Gaussian noise corruption. The NC values after attacks are all above 0.8 in the experiments so that the copyright can easily be distinguished.