A General Framework for Incorporating Time–Frequency Domain Sparsity in Multichannel Speech Dereverberation

Jukic A, van Waterschoot T, Gerkmann T, Doclo S. A General Framework for Incorporating Time–Frequency Domain Sparsity in Multichannel Speech Dereverberation. J Audio Eng Soc. 2017;65(1/2):17-30. doi:10.17743/jaes.2016.0064

@article{Jukic2017_18540,
  author = {Jukic, Ante and van Waterschoot, Toon and Gerkmann, Timo and Doclo, Simon},
  title = {{A General Framework for Incorporating Time–Frequency Domain Sparsity in Multichannel Speech Dereverberation}},
  journal = {Journal of the Audio Engineering Society},
  volume = {65},
  number = {1/2},
  pages = {17--30},
  year = {2017},
  month = jan,
  publisher = {Audio Engineering Society},
  doi = {10.17743/jaes.2016.0064},
  url = {https://doi.org/10.17743/jaes.2016.0064}
}

TY  - JOUR
TI  - A General Framework for Incorporating Time–Frequency Domain Sparsity in Multichannel Speech Dereverberation
AU  - Jukic, Ante
AU  - van Waterschoot, Toon
AU  - Gerkmann, Timo
AU  - Doclo, Simon
T2  - Journal of the Audio Engineering Society
J2  - J. Audio Eng. Soc.
VL  - 65
IS  - 1/2
SP  - 17
EP  - 30
PY  - 2017
DA  - 2017/01/06
DO  - 10.17743/jaes.2016.0064
UR  - https://doi.org/10.17743/jaes.2016.0064
PB  - Audio Engineering Society
LA  - en
AB  - Effective speech dereverberation is a prerequisite in such applications as hands-free telephony, voice-based human-machine interfaces, and hearing aids. Blind multichannel speech dereverberation methods based on multichannel linear prediction (MCLP) can estimate the dereverberated speech component without any knowledge of the room acoustics. This can be achieved by estimating and subtracting the undesired reverberant component from the reference microphone signal. This report presents a general framework that exploits sparsity in the time–frequency domain of a MCLP-based speech dereverberation. The framework combines a wideband or a narrowband signal model with either an analysis or a synthesis sparsity prior, and generalizes state-of-the-art MCLP-based speech dereverberation methods.
ER  -