Comments (5)
dansuh17
commented on May 28, 2024
1
+1, I suggest a more general structure commonly used in many computer vision datasets (like ImageNet), as: recordings/<digit>/<speaker>_<variation>.wav, following the structure <data_root>/<class_label>/<id>.<ext>.
from free-spoken-digit-dataset.
Jakobovski
commented on May 28, 2024
How would you like to organize the recordings?
from free-spoken-digit-dataset.
cesarsouza
commented on May 28, 2024
I would say that the simplest way would be to organize them hierarchically as recordings/<digit>/<speaker>/<digit>_<speaker>_<variation>.wav.
from free-spoken-digit-dataset.
Mistobaan
commented on May 28, 2024
+1, are the files also added using git lfs?
from free-spoken-digit-dataset.
Jakobovski
commented on May 28, 2024
@dansuh17 Feel free to contribute and I will accept the MR
from free-spoken-digit-dataset.
Related Issues (20)
- Normalize the recordings to have the same number of channels HOT 6
- New recordings are badly truncated HOT 8
- problem of 8bit&16bit HOT 4
- .wav encoding for speaker Nicolas not consistent with other speakers HOT 2
- adding more numbers HOT 3
- About reference HOT 3
- zero wav files too small to be read in python HOT 5
- How can we record 8KHz Mono WAV format file for Digit Classification? HOT 1
- License HOT 2
- RFI HOT 2
- Dataset download HOT 1
- Add other languages HOT 2
- How to perform 1D wavelet scattering transform on this dataset
- MAINT Update Zenodo and Tensorflow versions HOT 1
- DOI HOT 1
- IndexError when I run "ds.spectrograms[0].numpy()"
- View
- Gerrr
- The dataset contains 1501 recordings HOT 4
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from free-spoken-digit-dataset.