Skip to main content
placeholder image

Single-channel speech separation by including spectral structure information within non-negative matrix factorization

Conference Paper


Abstract


  • This paper proposes a novel extension on Non-negative Matrix Factorization (NMF) scheme for the separation of single channel speech mixtures, where we impose a post-sparse model on the original weight matrix derived from a previously proposed coherence-constrained NMF model. The approach considers both the modeling ability of NMF basis functions for each source as well as the ability of these basis functions to achieve accurate separation performance. Compared with latest associated NMF models for source separation, the results of our model indicate promising advantages, in terms of both objective source separation measures and Perceptual Evaluation of Speech Quality (PESQ) evaluations.

Publication Date


  • 2015

Citation


  • Y. Feng, C. Ritz, et al "Single-channel speech separation by including spectral structure information within non-negative matrix factorization," in Signal and Information Processing (ChinaSIP), 2015 IEEE China Summit and International Conference on, 2015, pp. 620-624.

Scopus Eid


  • 2-s2.0-84957591770

Ro Metadata Url


  • http://ro.uow.edu.au/eispapers/4369

Start Page


  • 620

End Page


  • 624

Abstract


  • This paper proposes a novel extension on Non-negative Matrix Factorization (NMF) scheme for the separation of single channel speech mixtures, where we impose a post-sparse model on the original weight matrix derived from a previously proposed coherence-constrained NMF model. The approach considers both the modeling ability of NMF basis functions for each source as well as the ability of these basis functions to achieve accurate separation performance. Compared with latest associated NMF models for source separation, the results of our model indicate promising advantages, in terms of both objective source separation measures and Perceptual Evaluation of Speech Quality (PESQ) evaluations.

Publication Date


  • 2015

Citation


  • Y. Feng, C. Ritz, et al "Single-channel speech separation by including spectral structure information within non-negative matrix factorization," in Signal and Information Processing (ChinaSIP), 2015 IEEE China Summit and International Conference on, 2015, pp. 620-624.

Scopus Eid


  • 2-s2.0-84957591770

Ro Metadata Url


  • http://ro.uow.edu.au/eispapers/4369

Start Page


  • 620

End Page


  • 624