Publication
] Universal and Non-universal Features of Musical Pitch Perception Revealed by Singing. Current Biology (2019). doi:10.1016/j.cub.2019.08.020
Time-dependent discrimination advantages for harmonic sounds suggest efficient coding for memory. Proceedings of the National Academy of Sciences 117, 32169 - 32180 (2020).
ThreeDWorld: A Platform for Interactive Multi-Modal Physical Simulation. arXiv (2020). at <https://arxiv.org/abs/2007.04954>
2007.04954.pdf (7.06 MB)
2007.04954.pdf (7.06 MB) A task-optimized neural network replicates human auditory behavior, predicts brain responses, and reveals a cortical processing hierarchy. Neuron 98, (2018).
Statistics of natural reverberation enable perceptual separation of sound and space. Proceedings of the National Academy of Sciences 113, E7856 - E7865 (2016).
A perceptually inspired generative model of rigid-body contact sounds. Proceedings of the 22nd International Conference on Digital Audio Effects (DAFx-19) (2019).
A neural population selective for song in human auditory cortex. Current Biology (2022). doi:10.1016/j.cub.2022.01.069 mmc2.pdf (9.52 MB)
mmc2.pdf (9.52 MB) Learning Mid-Level Auditory Codes from Natural Sound Statistics. Neural Computation 30, 631-669 (2018).
Invariance to background noise as a signature of non-primary auditory cortex. Nature Communications 10, (2019).
Illusory sound texture reveals multi-second statistical completion in auditory scene analysis. Nature Communications 10, (2019).
Harmonicity aids hearing in noise. Attention, Perception, & Psychophysics (2022). doi:10.3758/s13414-021-02376-0
Ecological origins of perceptual grouping principles in the auditory system. Proceedings of the National Academy of Sciences 116, 25355 - 25364 (2019).
Divergence in the functional organization of human and macaque auditory cortex revealed by fMRI responses to harmonic tones. Nature Neuroscience (2019). doi:10.1038/s41593-019-0410-7
Deep neural network models reveal interplay of peripheral coding and stimulus statistics in pitch perception. Nature Communications 12, (2021). s41467-021-27366-6.pdf (5.25 MB)
s41467-021-27366-6.pdf (5.25 MB) Deep neural network models of sound localization reveal how perception is adapted to real-world environments. Nature Human Behavior 6, 111–133 (2022). s41562-021-01244-z.pdf (7.22 MB)
s41562-021-01244-z.pdf (7.22 MB) Deep neural network models of sensory systems: windows onto the role of task constraints. Current Opinion in Neurobiology 55, 121 - 132 (2019).
Causal inference in environmental sound recognition. Cognition (2021). doi:10.1016/j.cognition.2021.104627
Untangling in Invariant Speech Recognition. Neural Information Processing Systems (NeurIPS 2019) (2019). 9583-untangling-in-invariant-speech-recognition.pdf (2.09 MB)
9583-untangling-in-invariant-speech-recognition.pdf (2.09 MB) Metamers of neural networks reveal divergence from human perceptual systems. NIPS 2019 (2019). at <https://papers.nips.cc/paper/9198-metamers-of-neural-networks-reveal-divergence-from-human-perceptual-systems> Feather_etal_2019_NeurIPS_metamers.pdf (4.7 MB)
Feather_etal_2019_NeurIPS_metamers.pdf (4.7 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 Uninformative Stimuli in the Auditory System. Association for Otolaryngology Mid-Winter Meeting (2017).
Lossy Compression of Sound Texture by the Human Auditory System. Society for Neuroscience Meeting (2016).
Learning Mid-Level Codes for Natural Sounds. Advances and Perspectives in Auditory Neuroscience (2016). APAN_large_JHM kopia.pdf (19.74 MB)
APAN_large_JHM kopia.pdf (19.74 MB) Learning Mid-Level Codes for Natural Sounds. Association for Otolaryngology Mid-Winter Meeting (2017).
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>