A Harmonic-Based Biologically Inspired Approach to Monaural Speech Separation

作者：Rabiee Azam^*; Setayeshi Saeed; Lee Soo Young

来源：IEEE Signal Processing Letters, 2012, 19(9): 559-562.

DOI：10.1109/LSP.2012.2206382

• Biologically inspired
• computational auditory scene analysis
• monaural speech separation

This letter proposes a computational auditory scene analysis (CASA) model for monaural speech separation. In this model, we integrate three biologically inspired approaches for: auditory spectrogram generation, analysis of its spectro-temporal content, and tracking its harmonic structure. In a top-down process, the estimated ideal binary mask (EIBM) is calculated using the spectral amplitude of the extracted spectrograms to enhance the harmonic filters for separation. Experimental results showed that our model outperformed the harmonic magnitude suppression technique in both signal-to-interference ratio and percentage of crosstalk. Moreover, the result is comparable with a current state-of-the-art system.

• 出版日期2012-9