Ambisonics, a popular format for spatial audio, involves encoding signals from spherical microphone arrays. Regularization is crucial to balance noise amplification and distortion in Ambisonics encoding. The study explores the sensitivity of Ambisonics neural networks to various levels of regularization and demonstrates the benefits of incorporating regularization information. Speaker localization algorithms based on DNN-DPD are evaluated for their performance under different regularization levels, emphasizing the significance of informed regularization strategies.
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by Bar Shaybet,... at arxiv.org 03-01-2024
https://arxiv.org/pdf/2402.18968.pdfDeeper Inquiries