Bangla Handwriting Resource Generation and Recognition Using Deep Learning Algorithms

Maintaining cultural and linguistic diversity is a challenge in an increasingly digital world. For a language like Bangla, with a rich script and heritage, preserving the essence of handwritten text is crucial. The research employs a Deep Learning algorithm, to decipher the nuances of handwritten Bangla script. The algorithm learns to mimic the fluid strokes, unique characters, and artistic nuances intrinsic to handwritten Bangla text through extensive training on the authentic dataset. To democratize the use of this technology, a user-friendly model interface for generating handwritten Bangla text is developed. This model allows users, regardless of technical expertise, to seamlessly recognize digital text into beautiful handwritten Bangla imagery. However, preserving the essence of Bangla's handwritten beauty is not just an act of conservation; it's a testament to our commitment to cultural diversity. The paper addresses this challenge by proposing a novel approach to recognizing digital Bangla text into handwritten Bangla text in image format, leveraging an authentic Bangla dataset.