TITLE:
Low-Rank Sparse Representation with Pre-Learned Dictionaries and Side Information for Singing Voice Separation
AUTHORS:
Chenghong Yang, Hongjuan Zhang
KEYWORDS:
Singing Voice Separation, Low-Rank and Sparse, Dictionary Learning
JOURNAL NAME:
Advances in Pure Mathematics,
Vol.8 No.4,
April
24,
2018
ABSTRACT: At present, although the human speech separation has
achieved fruitful results, it is not ideal for the separation of singing and
accompaniment. Based on low-rank and sparse optimization theory, in this paper,
we propose a new singing voice separation algorithm called Low-rank, Sparse
Representation with pre-learned dictionaries and side Information (LSRi). The
algorithm incorporates both the vocal and instrumental spectrograms as sparse
matrix and low-rank matrix, meanwhile combines pre-learning dictionary and the
reconstructed voice spectrogram form the annotation. Evaluations on the iKala
dataset show that the proposed methods are effective and efficient for singing
voice separation.