Harmonic Beamformers for Non-Intrusive Speech Intelligibility Prediction

Charlotte Sørensen, Jesper B. Boldt, Mads G. Christensen


In recent years, research into objective speech intelligibility measures has gained increased interest as a tool to optimize speech enhancement algorithms. While most intelligibility measures are intrusive, i.e., they require a clean reference signal, this is rarely available in real-time applications. This paper proposes two non-intrusive intelligibility measures, which allow using the intrusive short-time objective intelligibility (STOI) measure without requiring access to the clean signal. Instead, a reference signal is obtained from the degraded signal using either a fixed or an adaptive harmonic spatial filter. This reference signal is then used as input to STOI. The experimental results show a high correlation between both proposed non-intrusive speech intelligibility measures and the original intrusively computed STOI scores.


 DOI: 10.21437/Interspeech.2019-2929

Cite as: Sørensen, C., Boldt, J.B., Christensen, M.G. (2019) Harmonic Beamformers for Non-Intrusive Speech Intelligibility Prediction. Proc. Interspeech 2019, 4260-4264, DOI: 10.21437/Interspeech.2019-2929.


@inproceedings{Sørensen2019,
  author={Charlotte Sørensen and Jesper B. Boldt and Mads G. Christensen},
  title={{Harmonic Beamformers for Non-Intrusive Speech Intelligibility Prediction}},
  year=2019,
  booktitle={Proc. Interspeech 2019},
  pages={4260--4264},
  doi={10.21437/Interspeech.2019-2929},
  url={http://dx.doi.org/10.21437/Interspeech.2019-2929}
}