Sound ?eld reproduction (SFR) applied to microphone array recordings can be de?ned as an inverse problem. A typical issue is the resulting spatial source signal distribution. A least-square approach with solution 2-norm regularization will activate all sources. To circumvent such issues, sparsity-based regularization offers promising advantages. However, this can result in too sparse solutions. A promising avenue is based on structured-sparsity for prede?ned groups of reproduction sources. To this end, the group lasso was recently investigated without overlapping group. Its inability to deal with overlapping groups is a limitation. This paper presents the latent group lasso (LGL) where group-level sparsity is induced for overlapping groups. Theoretical results of LGL are successfully compared to other SFR results for sparsity-inducing norms.

Authors: Gauthier, Philippe-Aubert; Grandjean, Pierre; Berry Alain
Affiliations: University of Sherbrooke, Sherbrooke, Quebec, Canada; Centre for Interdisciplinary Research in Music, Media, and Technology, McGill University, Montreal, Quebec, Canada(See document for exact affiliation information.)
AES Conference: 2018 AES International Conference on Spatial Reproduction - Aesthetics and Science (July 2018)
Paper Number: P9-1
Publication Date: July 30, 2018
Session Subject: Sound field reproduction; Structured sparsity; Sparsity; Loudspeaker array; Latent Group; Lasso; Elastic-net

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