Room Acoustic System Identification Using Orthonormal Basis Function Models

Vairetti G, De Sena E, Catrysse M, Jensen SH, Moonen M, van Waterschoot T. Room Acoustic System Identification Using Orthonormal Basis Function Models. In: AES Conference: 60th International Conference: Dereverberation and Reverberation of Audio, Music, and Speech. Audio Engineering Society; 2016. Paper 7-3. Available from: https://aes.org/publications/elibrary-page/?id=18086

@inproceedings{Vairetti2016_18086,
  author = {Vairetti, Giacomo and De Sena, Enzo and Catrysse, Michael and Jensen, Søren H. and Moonen, Marc and van Waterschoot, Toon},
  title = {{Room Acoustic System Identification Using Orthonormal Basis Function Models}},
  booktitle = {AES Conference: 60th International Conference: Dereverberation and Reverberation of Audio, Music, and Speech},
  note = {Paper 7-3},
  year = {2016},
  month = jan,
  publisher = {Audio Engineering Society},
  url = {https://aes.org/publications/elibrary-page/?id=18086}
}

TY  - CPAPER
TI  - Room Acoustic System Identification Using Orthonormal Basis Function Models
AU  - Vairetti, Giacomo
AU  - De Sena, Enzo
AU  - Catrysse, Michael
AU  - Jensen, Søren H.
AU  - Moonen, Marc
AU  - van Waterschoot, Toon
T2  - AES Conference: 60th International Conference: Dereverberation and Reverberation of Audio, Music, and Speech
M1  - Paper 7-3
PY  - 2016
DA  - 2016/01/06
UR  - https://aes.org/publications/elibrary-page/?id=18086
PB  - Audio Engineering Society
LA  - en
AB  - Parametric modeling is used in all those acoustic signal enhancement applications that require to model and identify a room impulse response (RIR) in a compact yet accurate way. Fixed-pole models based on orthonormal basis functions (OBFs) provide advantages over all-zero and pole-zero models. The parameters of an OBF model can be estimated from a measured target RIR by a scalable matching pursuit algorithm called OBF-MP. However, a measurement for the RIR is usually not available, and the model parameters should be estimated from input-output data. This paper introduces a block-based version of OBF-MP for the modeling and identification of room acoustic systems, which represents an intermediate step towards a sample-based recursive implementation of the algorithm. Simulation results show modeling capabilities comparable with the original OBF-MP.
ER  -