Joint Amplitude and Phase Refinement for Monaural Source Separation

Yoshiki Masuyama, Kohei Yatabe, Kento Nagatomo, Yasuhiro Oikawa

Research output: Contribution to journalArticlepeer-review

Abstract

Monaural source separation is often conducted by manipulating the amplitude spectrogram of a mixture (e.g., via time-frequency masking and spectral subtraction). The obtained amplitudes are converted back to the time domain by using the phase of the mixture or by applying phase reconstruction. Although phase reconstruction performs well for the true amplitudes, its performance is degraded when the amplitudes contain error. To deal with this problem, we propose an optimization-based method to refine both amplitudes and phases based on the given amplitudes. It aims to find time-domain signals whose amplitude spectrograms are close to the given ones in terms of the generalized alpha-beta divergences. To solve the optimization problem, the alternating direction method of multipliers (ADMM) is utilized. We confirmed the effectiveness of the proposed method through speech-nonspeech separation in various conditions.

Original languageEnglish
Article number9226071
Pages (from-to)1939-1943
Number of pages5
JournalIEEE Signal Processing Letters
Volume27
DOIs
Publication statusPublished - 2020

Keywords

  • Phase reconstruction
  • alpha-beta divergences
  • mixture consistency
  • spectrogram consistency

ASJC Scopus subject areas

  • Signal Processing
  • Electrical and Electronic Engineering
  • Applied Mathematics

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