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---
license: mit
task_categories:
- audio-to-audio
language:
- en
---
# Dataset Card for LenslessMic Version of N(0,1) Random Dataset
## Dataset Summary
A LenslessMic version of the N(0,1) random images dataset from the
["LenslessMic: Audio Encryption and Authentication via Lensless Computational Imaging"](https://arxiv.org/abs/2509.16418) paper.
The dataset can be used to train a codec-agnostic reconstruction algorithm.
| Partition | # Audio | # Frames |
|--------------|---------|----------|
| train | 200 | 30000 |
**Note**: We split dataset into 200 files, however, there are no actual audio files. Only frames are used.
To download the dataset and work with it, use our [official repository](https://github.com/Blinorot/LenslessMic).
Dataset is collected using [DigiCam](https://arxiv.org/abs/2502.01102). Setup configuration:
| Parameter | Value |
|-------------------------------------------|--------------------|
| Screen Size | [1920, 1200] |
| Screen Pixel-Pitch | 0.27 mm |
| Screen-To-Mask Distance | 30e-2 m |
| Sensor Size | [4056, 3040] |
| Sensor Size Downsample Coefficient | 8 |
| Sensor Pixel-Pitch | 1.55 × 10⁻⁶ m |
| Mask-To-Sensor Distance | ≈ 4e-3 m |
| Image size on the Screen (256 case) | 928 × 928 |
| Image size on the Screen (288 case) | 1044 × 1044 |
| Vertical Shift on the Screen (256 case) | -23 |
| Vertical Shift on the Screen (288 case) | -20 |
| Number of masks | 100 |
| Mask Aperture Shape (for 1/3 channels) | [18, 24] |
| Mask Center | [55, 77] |
For other configuration, please refer to the codebase above.
## Dataset Structure
Dataset is structured in the following format:
```
.
└── partition_name
└── image_size # 16x16 or 32x32
├── lensed # lensed version of the video representation
| └── filename_i.mkv # normalized video representation of i-th audio file using this codec
└── lensless_measurement # lensless version captured using LenslessMic
├── filename_i.mkv # lensless video of the i-th audio file
├── filename_i.txt # label 'j' of the mask from the masks dir used for this video
└── masks # masks for the lensless camera
└── mask_j.npy # mask pattern
```
Apart from other LenslessMic datasets, this one does not use any audio codecs. These are just random images from N(0,1).
The dataset can be used to train a codec-agnostic reconstruction algorithm. No min/max vals are used (set to 0 and 1).
Some codecs have different types of lensless measurements:
1. `lensless_measurement`: standard version. Resizes images in a screen in a such a way that they have size 256x256 on the sensor.
Region of interest for the reconstruction for this dataset is:
| Sensor Image Size | Top Left Corner | Height | Width |
| ----------------- | --------------- | ------ | ----- |
| 256 x 256 | [65, 118] | 256 | 256 |
## Citation
If you use this dataset, please cite it as follows:
```bibtex
@article{grinberg2025lenslessmic,
title = {LenslessMic: Audio Encryption and Authentication via Lensless Computational Imaging},
author = {Grinberg, Petr and Bezzam, Eric and Prandoni, Paolo and Vetterli, Martin},
journal = {arXiv preprint arXiv:2509.16418},
year = {2025},
}
```
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