Cascaded AM Tuning for Sound Recognition

dataset

posted on 2019-03-29, 04:17 authored by Takuya KoumuraTakuya Koumura, Hiroki Terashima, Shigeto Furukawa

Dataset for "Cascaded Tuning to Amplitude Modulation for Natural Sound Recognition" by Takuya Koumura, Hiroki Terashima, and Shigeto Furukawa, Journal of Neuroscience 10 July 2019, 39 (28) 5517-5533.

Unzip the 7z files, put them in a single directory named "cascaded-am-tuning-for-sound-recognition", and put this in the same directory as the codes.

The codes are available at

https://github.com/cycentum/cascaded-am-tuning-for-sound-recognition

The directories ESC50 and TIMIT contain results of sound recognition and single unit recording in 39 models trained in this study. The directory am-meta-analysis contains the results of meta-analysis of neurophysiology papers.

Funding

JSPS KAKENHI Grant Number JP15H05915 (Grant-in-Aid for Scientific Research on Innovative Areas "Innovative SHITSUKSAN Science and Technology")

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Keywords

auditory system sound recognition amplitude modulation modulation transfer function single unit recording deep neural network Neuroscience

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CC BY 4.0

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