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Bangla Sign Language Dataset (BdSL40) comprises of 611 videos over 40 BdSL words with 8 to 22 video clips per word.

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BdSL40 Dataset

This Bangla Sign Language Dataset BdSL40 comprises of 611 videos over 40 BdSL words with 8 to 22 video clips per word.

AI for Bangla 2.0

This project received an Honorable Mention at the AI for Bangla 2.0 Competition, under team name -- Silent Sentinels.

Dataset Link

BdSL40 Video
BdSL40 Frames

ISL to BDSL Mapping

ISL-to-BDSL. This mapping was created according to BdSL Dictionary and ISL Dataset. It is relatively easy to reproduce BdSL40 from ISL by following the mapping.

Kaggle Notebook

Training_on_BdSL40

Dataset Properties

Criterion Count
Videos 611
Words 40
Label Count Label Count
new 21 bad 21
lawyer 14 teacher 14
yesterday 14 time 15
friend 20 i 21
you 21 telephone 14
ring 14 winter 14
brown 21 skirt 19
pant 20 shoes 20
camera 14 heavy 8
soap 14 book 14
india 21 quiet 21
deaf 8 rich 8
thick 8 money 14
cow 21 fulfill 8
cheap 8 straight 8
life 8 more 21
crane 20 shirt 20
noon 14 bed 14
square 14 glad 8
tortoise 20 student 14

Samples

Label: Student

Alt_test

Label: Tortoise

Alt_test

Preprocessing

VideoResnet requires videos to be sampled into images and cropped to a square ratio. 32 frames are sampled from each video and the height and width are set to 100 pixels by default.

Usage:

python Preprocessing/preprocessing.py [path_to_dataset] [path_to_save_images]

Hyperparameters

The following hyperparameters are set by default.

"num_epochs": 120,
"learning_rate": 5e-5,
"batch_size": 64,
"h": 100,
"w": 100,
"mean": [0.5, 0.5, 0.5],
"std":  [0.5, 0.5, 0.5],
"total_frames": 32,
"start_skip": 6,
"end_skip": 8,
"batch_size": 64,
"num_classes": 40,
"test_ratio": 0.2

Training

Usage:

python Training/training.py [path_to_save_images]

Results after Training

Accuracy 82.93%

Result2

Acknowledgements

This dataset is adapted from by INCLUDE by Sridhar et al under the Creative Commons 4.0 license.

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Bangla Sign Language Dataset (BdSL40) comprises of 611 videos over 40 BdSL words with 8 to 22 video clips per word.

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