Call for Papers EURASIP Journal on Audio, Speech, and Music Processing Special Issue on Sparse Modeling for Speech and Audio Processing

Sparse modeling and compressive sensing are rapidly developing fields in a variety of signal processing and machine learning conferences, focused on the problems of variable selection in high-dimensional datasets and signal reconstruction from few training examples. With the increasing amount of high-dimensional speech and audio data available, the need to efficiently represent and search through these data spaces is becoming of vital importance. The challenges arise from selecting highly predictive signal features and adaptively finding a dictionary which best represents the signal. Overcoming these challenges is likely to require efficient and effective algorithms, mainly focused on l1-regularized optimization, basis pursuit, Lasso sparse regression, missing data problem and various extensions. Despite the significant advances in the fields, there are a number of open issues remain when realizing sparse model in real-life applications, e.g. stability and interpretability of sparse models, model selection, group/fused sparsity, and evaluation of the results. Furthermore, sparse modeling has ubiquitous applications in speech and audio processing areas, including dimensionality reduction, model regularization, speech/audio compression/reconstruction, acoustic/audio feature selection, acoustic modeling, speech recognition, blind source separation, and many others. Our goal aims to come up with a set of new algorithms/applications and to advance the state of the arts in speech and audio processing. In light of the sufficiently growing research activities and their importance, we openly invite papers describing various aspects of sparsity modeling and related techniques as well as their successful applications. Submissions must not have been previously published and must have specific connection to audio, speech, and music processing. The topics of particular interest will include, but are not limited to: • Sparse representation and compressive sensing • Sparse modeling and regression • Sparse modeling for model regularization • Sparse modeling for speech recognition • Sparse modeling for language processing • Sparse modeling for source separation • Sparse modeling for music processing • Deep learning for sparse models • Practical applications of sparse modeling • Machine learning algorithms, techniques and applications Before submission authors should carefully read over the journal’s Instructions for Authors, which are located at http://asmp.eurasipjournals.com/authors/instructions. Prospective authors should submit an electronic copy of their complete manuscript through the SpringerOpen submission system at http://asmp.eurasipjournals.com/manuscript, according to the following timetable:

Manuscript Due: June 15, 2012

First Round of Reviews: September 1, 2012

Publication Date: December 1, 2012

Guest editors: Jen-Tzung Chien (E-mail: jtchien@mail.ncku.edu.tw) National Cheng Kung University, Tainan, Taiwan Bhuvana Ramabhadran (E-mail: bhuvana@us.ibm.com) IBM T. J. Watson Research Center, Yorktown Heights, NY, USA Tomoko Matsui (E-mail: tmatsui@ism.ac.jp) The Institute of Statistical Mathematics, Tokyo, Japan