cascaded-am-tuning-for-sound-recognition
Codes for "Cascaded Tuning to Amplitude Modulation for Natural Sound Recognition" by Takuya Koumura, Hiroki Terashima, and Shigeto Furukawa.
Reference
Koumura T, Terashima H, Furukawa S (2019) Cascaded Tuning to Amplitude Modulation for Natural Sound Recognition. J Neurosci 39(28):5517–5533. DOI: https://doi.org/10.1523/JNEUROSCI.2914-18.2019
Dependencies
- Python 3
- Chainer https://chainer.org/
- soundfile https://pypi.org/project/SoundFile/
Datasets
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The directory tree should look like this:
cascaded-am-tuning-for-sound-recognition ├── cascaded-am-tuning-for-sound-recognition │ ├── am-meta-analysis │ │ └── cumulative │ │ ├── Atencio2010 │ │ │ ├── txt files │ │ │ └── ... │ │ ├── Bartlett2007 │ │ └── (more directories...) │ ├── ESC50 │ │ ├── ESC-50 │ │ │ ├── 101 - Dog │ │ │ ├── ogg files │ │ │ └── ... │ │ │ ├── 102 - Rooster │ │ │ └── (more directories...) │ │ ├── info.txt │ │ └── Results │ │ ├── Result0 │ │ │ ├── Architecture.txt │ │ │ ├── ConfusionMatrix.txt │ │ │ ├── Params.txt │ │ │ ├── Response │ │ │ │ ├── Am │ │ │ │ └── Am0 │ │ │ └── TrainedModel │ │ ├── Result1 │ │ │ └── (same filenames as in Result0) │ │ └── (more directories...) │ └── TIMIT │ ├── Results │ │ ├── Result0 │ │ │ ├── Architecture.txt │ │ │ ├── ConfusionMatrix.txt │ │ │ ├── Params.txt │ │ │ ├── Response │ │ │ │ ├── Am │ │ │ │ └── Am0 │ │ │ └── TrainedModel │ │ ├── Result1 │ │ │ └── (same filenames as in Result0) │ │ └── (more directories...) │ └── TIMIT │ ├── TEST │ │ ├── DR1 │ │ ├── DR2 │ │ └── (more directories...) │ └── TRAIN │ ├── DR1 │ └── (more directories...) ├── draw_mtf_esc50.py ├── draw_mtf_timit.py └── (more py files...)(It may be a bit confusing because directories with the same name appears twice...)
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ESC-50: Dataset for Environmental Sound Classification https://doi.org/10.7910/DVN/YDEPUT
- Download audio files and put them in the directory "ESC50" indluced in the above dataset at figshare
- Note: our code is built for the older version of ESC-50 with ogg format, in which folder organizations are slightly different from the current version at https://github.com/karoldvl/ESC-50
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TIMIT Acoustic-Phonetic Continuous Speech Corpus https://catalog.ldc.upenn.edu/LDC93S1
- Download audio files and put them in the directory "TIMIT" indluced in the above dataset at figshare
License
Please see LICENSE.