Publication
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Filters: Author is Josh H. McDermott [Clear All Filters]
Learning Mid-Level Auditory Codes from Natural Sound Statistics. (2017).
MlynarskiMcDermott_Memo060.pdf (7.11 MB)

Learning Mid-Level Codes for Natural Sounds. Association for Otolaryngology Mid-Winter Meeting (2017).
A library of real-world reverberation and a toolbox for its analysis and measurement. Annual Meeting of Acoustical Society of America (2017).
Lossy Compression of Uninformative Stimuli in the Auditory System. Association for Otolaryngology Mid-Winter Meeting (2017).
Environmental statistics enable perceptual separation of sound and space. Speech and Audio in the Northeast (2016).
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>
Wiktor_COSYNE_2015_hierarchy_final.pdf (2.52 MB)

Learning Mid-Level Codes for Natural Sounds. Advances and Perspectives in Auditory Neuroscience (2016).
APAN_large_JHM kopia.pdf (19.74 MB)

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
Lossy Compression of Sound Texture by the Human Auditory System. Society for Neuroscience Meeting (2016).
Statistics of natural reverberation enable perceptual separation of sound and space. Proceedings of the National Academy of Sciences 113, E7856 - E7865 (2016).
Visually indicated sounds. Conference on Computer Vision and Pattern Recognition (2016).
Owens_etal_2016_visually_indicated_sounds_CVPR.pdf (7.57 MB)
