Publication

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In Press
Kell, A. J. E., Yamins, D. L. K., Shook, E. N., Norman-Haignere, S. V. & McDermott, J. H. A task-optimized neural network replicates human auditory behavior, predicts brain responses, and reveals a cortical processing hierarchy. Neuron 98, (In Press).
2019
Kell, A. J. E. & McDermott, J. H. Deep neural network models of sensory systems: windows onto the role of task constraints. Current Opinion in Neurobiology 55, 121 - 132 (2019).
2018
Mlynarski, W. & McDermott, J. H. Co-occurrence statistics of natural sound features predict perceptual grouping. Computational and Systems Neuroscience (COSYNE) (2018). at <http://www.cosyne.org/c/index.php?title=Cosyne_18>
Mlynarski, W. & McDermott, J. H. Co-occurrence statistics of natural sound features predict perceptual grouping. Computational and Systems Neuroscience (Cosyne) 2018 (2018).
Traer, J. & McDermott, J. H. Human inference of force from impact sounds: Perceptual evidence for inverse physics. Annual Meeting of the Acoustical Society 143, (2018).
Traer, J. & McDermott, J. H. Human recognition of environmental sounds is not always robust to reverberation. Annual Meeting of the Acoustical Society 143, (2018).
Mlynarski, W. & McDermott, J. H. Learning Mid-Level Auditory Codes from Natural Sound Statistics. Neural Computation 30, 631-669 (2018).
2017
Mlynarski, W. & McDermott, J. H. Adaptive Compression of Statistically Homogenous Sensory Signals. Computational and Systems Neuroscience (COSYNE) (2017).
Traer, J. & McDermott, J. H. Auditory Perception of Material and Force from Impact Sounds. Annual Meeting of Association for Research in Otolaryngology (2017).
Zhang, Z. et al. Generative modeling of audible shapes for object perception. The IEEE International Conference on Computer Vision (ICCV) (2017). at <http://openaccess.thecvf.com/content_iccv_2017/html/Zhang_Generative_Modeling_of_ICCV_2017_paper.html>
Traer, J. & McDermott, J. H. Investigating audition with a generative model of impact sounds. Annual Meeting of Acoustical Society of America (2017).
Mlynarski, W. & McDermott, J. H. Learning Mid-Level Auditory Codes from Natural Sound Statistics. (2017).PDF icon MlynarskiMcDermott_Memo060.pdf (7.11 MB)
Mlynarski, W. & McDermott, J. H. Learning Mid-Level Codes for Natural Sounds. Association for Otolaryngology Mid-Winter Meeting (2017).
Traer, J. & McDermott, J. H. A library of real-world reverberation and a toolbox for its analysis and measurement. Annual Meeting of Acoustical Society of America (2017).
Mlynarski, W. & McDermott, J. H. Lossy Compression of Uninformative Stimuli in the Auditory System. Association for Otolaryngology Mid-Winter Meeting (2017).
2016
Traer, J. & McDermott, J. H. Environmental statistics enable perceptual separation of sound and space. Speech and Audio in the Northeast (2016).
Mlynarski, W. & McDermott, J. H. Learning mid-level codes for natural sounds. Computational and Systems Neuroscience (Cosyne) 2016 (2016). at <http://www.cosyne.org/c/index.php?title=Cosyne2016_posters_2>PDF icon Wiktor_COSYNE_2015_hierarchy_final.pdf (2.52 MB)
Mlynarski, W. & McDermott, J. H. Learning Mid-Level Codes for Natural Sounds. Advances and Perspectives in Auditory Neuroscience (2016).PDF icon APAN_large_JHM kopia.pdf (19.74 MB)
Owens, A., Isola, P., McDermott, J. H., Freeman, W. T. & Torralba, A. Lecture Notes in Computer ScienceComputer Vision – ECCV 2016Ambient Sound Provides Supervision for Visual Learning. 14th European Conference on Computer Vision 801 - 816 (2016). doi:10.1007/978-3-319-46448-010.1007/978-3-319-46448-0_48
Mlynarski, W. & McDermott, J. H. Lossy Compression of Sound Texture by the Human Auditory System. Society for Neuroscience Meeting (2016).
Traer, J. & McDermott, J. H. Statistics of natural reverberation enable perceptual separation of sound and space. Proceedings of the National Academy of Sciences 113, E7856 - E7865 (2016).
Owens, A. et al. Visually indicated sounds. Conference on Computer Vision and Pattern Recognition (2016).PDF icon Owens_etal_2016_visually_indicated_sounds_CVPR.pdf (7.57 MB)