TY - GEN
T1 - Audio watermarking based on empirical mode decomposition and beat detection
AU - Teleşpan, Marius
AU - Schuller, Björn W.
N1 - Publisher Copyright:
© 2016 IEEE.
PY - 2016/5/18
Y1 - 2016/5/18
N2 - In the recent years a large number of methods have been proposed in order to reliably embed information into audio files. Despite their increased robustness against attacks, they tend to have a lot of redundancy due to a large number of bits used for majority voting due to disability to correctly select regions that are unlikely to be distorted by attacks. To overcome this, we propose a robust method for audio watermarking where Empirical Mode Decomposition and beat detection are used for detecting the locations for embedding the watermark. In order to find the embedding locations, we use a simplified psychoacoustic model to split the input into audible frequency bands and two phase comb filtering on those bands to find the beat metrical structure. Then, at each embedding location, we take several frames and decompose them into Intrinsic Mode Functions. In an extensive test, we show promising results on a selection of songs spanning over three musical genres.
AB - In the recent years a large number of methods have been proposed in order to reliably embed information into audio files. Despite their increased robustness against attacks, they tend to have a lot of redundancy due to a large number of bits used for majority voting due to disability to correctly select regions that are unlikely to be distorted by attacks. To overcome this, we propose a robust method for audio watermarking where Empirical Mode Decomposition and beat detection are used for detecting the locations for embedding the watermark. In order to find the embedding locations, we use a simplified psychoacoustic model to split the input into audible frequency bands and two phase comb filtering on those bands to find the beat metrical structure. Then, at each embedding location, we take several frames and decompose them into Intrinsic Mode Functions. In an extensive test, we show promising results on a selection of songs spanning over three musical genres.
KW - audio watermarking
KW - beat detection
KW - beat tracking
KW - empirical mode decomposition
KW - intrinsic mode function
UR - http://www.scopus.com/inward/record.url?scp=84973333817&partnerID=8YFLogxK
U2 - 10.1109/ICASSP.2016.7472052
DO - 10.1109/ICASSP.2016.7472052
M3 - Conference contribution
AN - SCOPUS:84973333817
T3 - ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings
SP - 2124
EP - 2128
BT - 2016 IEEE International Conference on Acoustics, Speech and Signal Processing, ICASSP 2016 - Proceedings
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 41st IEEE International Conference on Acoustics, Speech and Signal Processing, ICASSP 2016
Y2 - 20 March 2016 through 25 March 2016
ER -