1 research outputs found
Source Separation of Unknown Numbers of Single-Channel Underwater Acoustic Signals Based on Autoencoders
The separation of single-channel underwater acoustic signals is a challenging
problem with practical significance. Few existing studies focus on the source
separation problem with unknown numbers of signals, and how to evaluate the
performances of the systems is not yet clear. We propose a solution with a
fixed number of output channels to address these two problems, enabling it to
avoid the dimensional disaster caused by the permutation problem induced by the
alignment of outputs to targets. Specifically, we propose a two-step algorithm
based on autoencoders and a new performance evaluation method for situations
with mute channels. Experiments conducted on simulated mixtures of radiated
ship noise show that the proposed solution can achieve similar separation
performance to that attained with a known number of signals. The proposed
algorithm achieved competitive performance as two algorithms developed for
known numbers of signals, which is highly explainable and extensible and get
the state of the art under this framework.Comment: 14 pages, 4 figures, 3 tables. For codes, see
https://github.com/QinggangSUN/unknown_number_source_separatio