Multichannel NMF for source separation with ambisonic signals

Joonas Nikunen, Archontis Politis

Research output: Chapter in Book/Report/Conference proceedingConference contributionScientificpeer-review

1 Citation (Scopus)


This paper proposes a novel method for separation of sound sources with ambisonic signals using multichannel non-negative matrix factorization (MNMF) for source spectrogram estimation. We present a novel frequency-independent spatial covariance matrix (SCM) model for spherical harmonic (SH) domain signals which makes the MNMF parameter estimation framework computationally feasible up to 3rd order SH signals. The evaluation is done with simulated SH domain mixtures by measuring the separation performance using objective criteria and comparing the proposed method against SH domain beamforming. The proposed method improves average separation performance over beamforming with post-filtering when using 1st and 2nd order SH signals while at higher orders performance among all tested methods is similar.

Original languageEnglish
Title of host publication16th International Workshop on Acoustic Signal Enhancement, IWAENC 2018 - Proceedings
Number of pages5
ISBN (Electronic)9781538681510
Publication statusPublished - 2 Nov 2018
MoE publication typeA4 Article in a conference publication
EventInternational Workshop on Acoustic Signal Enhancement - Tokyo, Japan
Duration: 17 Sep 201820 Sep 2018
Conference number: 16


WorkshopInternational Workshop on Acoustic Signal Enhancement
Abbreviated titleIWAENC


  • Ambisonics
  • Multichannel NMF
  • Source separation

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