ISCA Archive Interspeech 2008
ISCA Archive Interspeech 2008

Psychoacoustically-motivated adaptive β-order generalized spectral subtraction based on data-driven optimization

Junfeng Li, Hui Jiang, Masato Akagi

To mitigate the performance limitations caused by the constant spectral order β in the traditional spectral subtraction methods, we previously presented an adaptive β-order generalized spectral subtraction (GSS) in which the spectral order β is updated in a heuristic way. In this paper, we propose a psychoacousticallymotivated adaptive β-order GSS, by considering that different frequency bands contribute different amounts to speech intelligibility (i.e., the band-importance function). Specifically, in this proposed adaptive β-order GSS, the tendency of spectral order β to change with the input local signal-to-noise ratio (SNR) is quantitatively approximated by a sigmoid function, which is derived through a data-driven optimization procedure by minimizing the intelligibility-weighted distance between the desired speech spectrum and its estimate. The inherent parameters of the sigmoid function are further optimized with the data-driven optimization procedure. Experimental results indicate that the proposed psychoacoustically-motivated adaptive β-order GSS yields great improvements over the traditional spectral subtraction methods with the intelligibility-weighted measures.


doi: 10.21437/Interspeech.2008-40

Cite as: Li, J., Jiang, H., Akagi, M. (2008) Psychoacoustically-motivated adaptive β-order generalized spectral subtraction based on data-driven optimization. Proc. Interspeech 2008, 171-174, doi: 10.21437/Interspeech.2008-40

@inproceedings{li08b_interspeech,
  author={Junfeng Li and Hui Jiang and Masato Akagi},
  title={{Psychoacoustically-motivated adaptive β-order generalized spectral subtraction based on data-driven optimization}},
  year=2008,
  booktitle={Proc. Interspeech 2008},
  pages={171--174},
  doi={10.21437/Interspeech.2008-40}
}