Werner Oomen
Philips
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Publication
Featured researches published by Werner Oomen.
IEEE Transactions on Signal Processing | 2003
Aweke Negash Lemma; Javier Francisco Aprea; Werner Oomen; L. van de Kerkhof
Audio watermarking techniques can be used to embed extra information into audio signals. The goal is to hide prespecified data carrying some information into the audio stream such that it is not audible to the human ear (i.e., transparent) and is, at the same time, resistant to removal attacks (i.e., robust). In the currently known watermarking systems, the above challenges are not always adequately resolved. We present an alternative audio watermarking technique that mitigates these and other related shortcomings. The system is referred to as modified audio signal keying (MASK). In MASK, the short-time envelope of the audio signal is modified in such a way that the change is imperceptible to the human listener. The MASK system can easily be tailored for a wide range of applications. Moreover, informal experimental results show that it has a good robustness and audibility behavior.
Eurasip Journal on Audio, Speech, and Music Processing | 2009
Albertus Cornelis Den Brinker; Jeroen Breebaart; Per Ekstrand; Jonas Engdegard; Fredrik Henn; Kristofer Kjörling; Werner Oomen; Heiko Purnhagen
In 2003 and 2004, the ISO/IEC MPEG standardization committee added two amendments to their MPEG-4 audio coding standard. These amendments concern parametric coding techniques and encompass Spectral Band Replication (SBR), Sinusoidal Coding (SSC), and Parametric Stereo (PS). In this paper, we will give an overview of the basic ideas behind these techniques and references to more detailed information. Furthermore, the results of listening tests as performed during the final stages of the MPEG-4 standardization process are presented in order to illustrate the performance of these techniques.
international conference on digital signal processing | 2002
Aweke Negash Lemma; Javier Francisco Aprea; Werner Oomen; L. van de Kerkhof
Audio watermarking techniques can be used to embed extra information into audio signals. The goal is to hide pre-specified data carrying some information into the audio stream such that it is not audible to the human ear (i.e., transparent) and is, at the same time, resistant to signal processing and removal attacks (i.e., robust). In the currently known watermarking systems, the above challenge is not always adequately resolved. This and other practical considerations such as complexity have motivated us to look into other alternatives to audio watermarking. In this paper, we present a new watermarking system referred to as MASK (modified audio signal keying) that has resulted from this study. In MASK, the short-term envelope of the audio signal is modified in such a way that the change is imperceptible to the human listener. Results of informal experiments do not only confirm this, but also show that MASK has a good robustness behavior.
Journal of the Acoustical Society of America | 2008
Steven van de Par; Jeroen Koppens; Ag Armin Kohlrausch; Werner Oomen
Perceptual audio coding achieves part of its coding efficiency by spectrally shaping the quantization noise such that it is masked by the audio signal to be encoded. In order to determine how much quantization noise is allowed within each frequency band and time interval a masking model is used to predict a masking curve specifying the maximally allowed quantization noise level within each frequency band. In most audio coders only spectral masking properties of the audio signal are used. The model by Dau et al. [J. Acoust. Soc. Am. 99, Vol. 3615, 1996] provides an interesting approach to also model temporal masking. Since this model operates as an artificial observer it only predicts whether the quantization noise is audible or not in the presence of the audio signal. In order to determine the most efficient quantization noise shape, the encoder needs to iteratively adapt the noise shape and evaluate each option with the model. This implies a highly computational complex encoding algorithm. In this contri...
Journal of The Audio Engineering Society | 2007
Jürgen Herre; Kristofer Kjörling; Jeroen Breebaart; Christof Faller; Sascha Disch; Heiko Purnhagen; Jeroen Koppens; Johannes Hilpert; Jonas Röden; Werner Oomen; Karsten Linzmeier; Kok Seng Chong
Journal of The Audio Engineering Society | 2008
Jeroen Breebaart; Jonas Engdegard; Cornelia Falch; Oliver Hellmuth; Johannes Hilpert; Andreas Hoelzer; Jeroen Koppens; Werner Oomen; Barbara Resch; Erik Gosuinus Petrus Schuijers; Leonid Terentiev
Journal of The Audio Engineering Society | 2005
Jeroen Breebaart; Jürgen Herre; Christof Faller; Jonas Röden; F Myburg; Sascha Disch; Heiko Purnhagen; Gerard Hotho; M Neusinger; C Kjörling; Werner Oomen
Journal of The Audio Engineering Society | 2003
Werner Oomen; Erik Gosuinus Petrus Schuijers; Bert den Brinker; Jeroen Breebaart
Archive | 2007
Johannes Hilpert; Karsten Linzmeier; Juergen Herre; Ralph Sperschneider; Andreas Hoelzer; Lars Villemoes; Jonas Engdegard; Heiko Purnhagen; Kristofer Kjoerling; Jeroen Breebaart; Werner Oomen
Archive | 2005
Matthias Neusinger; Jürgen Herre; Sascha Disch; Heiko Purnhagen; Kristofer Kjörling; Jonas Engdegard; Jeroen Breebaart; Erik Gosuinus Petrus Schuijers; Werner Oomen