Ricerc@Sapienza

The goal of this special issue is to understand how and to what extent novel computational intelligence techniques based on the emerging end-to-end learning paradigm can be efficiently employed in Digital Audio, in the light of all aforementioned aspects. In line with the mission of the IEEE Computational Intelligence Society Task Force in Computational Audio Processing (http://ieeeciscap.dii.univpm.it/), the organizers of this Special Issue have strived to bring the focus on the most recent advancements in the Computational Intelligence field, and on their applicability to Digital Audio problems from the end-to-end learning perspective. The Issue collects seven original contributions, which cover some of the aforementioned topics providing to the reader an insightful panoramic view of the most recent research achievements. The selection of the present papers is the result of a rigorous review procedure, where at least three independent reviewers were involved with each paper, and up to three review rounds were performed before final acceptance for publication. The special issues papers are briefly summarized.