Literature

[CGF+21]

Paolo Castellini, Nicola Giulietti, Nicola Falcionelli, Aldo Franco Dragoni, and Paolo Chiariotti. A neural network based microphone array approach to grid-less noise source localization. Applied Acoustics, 177:107947, 2021. doi:10.1016/j.apacoust.2021.107947.

[FZHX22]

Luoyi Feng, Ming Zan, Linsen Huang, and Zhongming Xu. A double-step grid-free method for sound source identification using deep learning. Applied Acoustics, 201:109099, 2022. doi:10.1016/j.apacoust.2022.109099.

[HS17]

Gert Herold and Ennes Sarradj. Performance analysis of microphone array methods. Journal of Sound and Vibration, 401:152–168, 2017.

[KHS19]

Adam Kujawski, Gert Herold, and Ennes Sarradj. A Deep Learning Method for Grid-Free Localization and Quantification of Sound Sources. The Journal of the Acoustical Society of America, 146(3):EL225–EL231, 2019. doi:10.1121/1.5126020.

[KPJS23]

Adam Kujawski, Art J. R. Pelling, Simon Jekosch, and Ennes Sarradj. A framework for generating large-scale microphone array data for machine learning. Multimedia Tools and Applications, 2023. doi:10.1007/s11042-023-16947-w.

[KPS23]

Adam Kujawski, Art J. R. Pelling, and Ennes Sarradj. Miracle - microphone array impulse response dataset for acoustic learning. 2023. doi:10.14279/depositonce-20106.

[KS22]

Adam Kujawski and Ennes Sarradj. Fast grid-free strength mapping of multiple sound sources from microphone array data using a transformer architecture. The Journal of the Acoustical Society of America, 152(5):2543–2556, 2022. doi:10.1121/10.0015005.

[Sar12]

E. Sarradj. Three-dimensional acoustic source mapping with different beamforming steering vector formulations. Advances in Acoustics and Vibration, 2012(292695):1–12, 2012. doi:10.1155/2012/292695.

[SH17]

Ennes Sarradj and Gert Herold. A python framework for microphone array data processing. Applied Acoustics, 116:50–58, 2017.