Full-Sphere Binaural Sound Source Localization by Maximum-Likelihood Estimation of Interaural Parameters

Hammond B, Jackson PJB. Full-Sphere Binaural Sound Source Localization by Maximum-Likelihood Estimation of Interaural Parameters. In: AES Convention 142. Audio Engineering Society; 2017. Paper 9771. Available from: https://aes.org/publications/elibrary-page/?id=18647

@inproceedings{Hammond2017_18647,
  author = {Hammond, Benjamin and Jackson, Philip J. B.},
  title = {{Full-Sphere Binaural Sound Source Localization by Maximum-Likelihood Estimation of Interaural Parameters}},
  booktitle = {AES Convention 142},
  note = {Paper 9771},
  year = {2017},
  month = may,
  publisher = {Audio Engineering Society},
  url = {https://aes.org/publications/elibrary-page/?id=18647}
}

TY  - CPAPER
TI  - Full-Sphere Binaural Sound Source Localization by Maximum-Likelihood Estimation of Interaural Parameters
AU  - Hammond, Benjamin
AU  - Jackson, Philip J. B.
T2  - AES Convention 142
M1  - Paper 9771
PY  - 2017
DA  - 2017/05/06
UR  - https://aes.org/publications/elibrary-page/?id=18647
PB  - Audio Engineering Society
LA  - en
AB  - Binaural recording technology offers an inexpensive, portable solution for spatial audio capture. In this paper a full-sphere 2D localization method is proposed that utilizes the Model-Based Expectation-Maximization Source Separation and Localization system (MESSL). The localization model is trained using a full-sphere head related transfer function dataset and produces localization estimates by maximum-likelihood of frequency-dependent interaural parameters. The model’s robustness is assessed using matched and mismatched HRTF datasets between test and training data, with environmental sounds and speech. Results show that the majority of sounds are estimated correctly with the matched condition in low noise levels; for the mismatched condition, a “cone of confusion” arises with albeit effective estimation of lateral angles. Additionally, the results show a relationship between the spectral content of the test data and the performance of the proposed method.
ER  -