Optimization and Evaluation of an Intelligibility-Improving Signal Processing Approach (IISPA) for the Hurricane Challenge 2.0 with FADE

Marc René Schädler


This contributions describes the “IISPA” submission to the Hurricane Challenge 2.0. The challenge organizers called for submissions of speech signals processed with the aim to improve their intelligibility in adverse listening conditions. They evaluated the submissions with matrix sentence tests in an international listening experiment. An intelligibility-improving signal processing approach (IISPA) inspired from research on speech perception of listeners with impaired hearing was designed. Its parameters were optimized with an objective intelligibility model, the simulation framework for auditory discrimination experiments (FADE). In FADE, a re-purposed automatic speech recognition (ASR) system is employed as a models for human speech recognition performance. The model predicted an improvement in speech recognition threshold (SRT) of approximately 5.0 dB due to the optimized IISPA. The processed speech signals were evaluated in the Hurricane Challenge 2.0. The measured improvements were language-dependent: up to 4.8 dB for the Spanish test, up to 3.8 dB for the German test, and up to 2.1 dB for the English test. The results show on the one hand the potential of using an ASR-based speech recognition model to optimize an intelligibility-improving signal processing scheme, and on the other hand the need for thorough listening experiments.


 DOI: 10.21437/Interspeech.2020-0093

Cite as: Schädler, M.R. (2020) Optimization and Evaluation of an Intelligibility-Improving Signal Processing Approach (IISPA) for the Hurricane Challenge 2.0 with FADE. Proc. Interspeech 2020, 1331-1335, DOI: 10.21437/Interspeech.2020-0093.


@inproceedings{Schädler2020,
  author={Marc René Schädler},
  title={{Optimization and Evaluation of an Intelligibility-Improving Signal Processing Approach (IISPA) for the Hurricane Challenge 2.0 with FADE}},
  year=2020,
  booktitle={Proc. Interspeech 2020},
  pages={1331--1335},
  doi={10.21437/Interspeech.2020-0093},
  url={http://dx.doi.org/10.21437/Interspeech.2020-0093}
}