{"about":{"site":"https://codewithpapers.app","non_affiliation":"Code with Papers and Syntology are not affiliated with, endorsed by, or sponsored by Papers with Code, Meta, or the pwc-archive mirror.","licence":"CC BY-SA 4.0","licence_url":"https://creativecommons.org/licenses/by-sa/4.0/legalcode","attribution":"https://codewithpapers.app/attribution","modified":"archive material modified by Syntology; see the attribution page"},"url":"/paper/pipeline-enabling-zero-shot-classification","title":"Pipeline Enabling Zero-shot Classification for Bangla Handwritten Grapheme","arxiv_id":null,"date":"2023-12-01","proceeding":"Proceedings of the First Workshop on Bangla Language Processing (BLP-2023) 2023 12","authors":["Linsheng Guo","Md Habibur Sifat","Tashin Ahmed"],"abstract":"This research investigates Zero-Shot Learning (ZSL), and proposes CycleGAN-based image synthesis and accurate label mapping to build a strong association between labels and graphemes. The objective is to enhance model accuracy in detecting unseen classes by employing advanced font image categorization and a CycleGAN-based generator. The resulting representations of abstract character structures demonstrate a significant improvement in recognition, accommodating both seen and unseen classes. This investigation addresses the complex issue of Optical Character Recognition (OCR) in the specific context of the Bangla language. Bangla script is renowned for its intricate nature, consisting of a total of 49 letters, which include 11 vowels, 38 consonants, and 18 diacritics. The combination of letters in this complex arrangement provides the opportunity to create almost 13,000 unique variations of graphemes, which exceeds the number of graphemic units found in the English language. Our investigation presents a new strategy for ZSL in the context of Bangla OCR. This approach combines generative models with careful labeling techniques to enhance the progress of Bangla OCR, specifically focusing on grapheme categorization. Our goal is to make a substantial impact on the digitalization of educational resources in the Indian subcontinent.","url_abs":"https://scholar.google.com/citations?view_op=view_citation&hl=en&user=aw_mTesAAAAJ&citation_for_view=aw_mTesAAAAJ:4DMP91E08xMC","url_pdf":"https://aclanthology.org/2023.banglalp-1.4.pdf","source":{"archive":"pwc-archive (Hugging Face), CC BY-SA 4.0","snapshot":"2025-07-28","licence_url":"https://creativecommons.org/licenses/by-sa/4.0/legalcode","row_kind":"abstracts"},"code_links":[],"tasks":[{"task_slug":"bangla-text-detection","task_name":"Bangla Text Detection"},{"task_slug":"classification-1","task_name":"Classification"},{"task_slug":"grapheme-detection","task_name":"Grapheme Detection"},{"task_slug":"handwritten-text-recognition","task_name":"Handwritten Text Recognition"},{"task_slug":"image-categorization","task_name":"Image Categorization"},{"task_slug":"image-generation","task_name":"Image Generation"},{"task_slug":"optical-character-recognition","task_name":"Optical Character Recognition"},{"task_slug":"optical-character-recognition","task_name":"Optical Character Recognition (OCR)"},{"task_slug":"text-detection","task_name":"Text Detection"},{"task_slug":"zero-shot-learning","task_name":"Zero-Shot Learning"},{"task_slug":null,"task_name":"zero-shot-classification"}],"methods":[{"method_slug":"batch-normalization","method_name":"Batch Normalization"},{"method_slug":"convolution","method_name":"Convolution"},{"method_slug":"cycle-consistency-loss","method_name":"Cycle Consistency Loss"},{"method_slug":"gan-least-squares-loss","method_name":"GAN Least Squares Loss"},{"method_slug":"instance-normalization","method_name":"Instance Normalization"},{"method_slug":"patchgan","method_name":"PatchGAN"},{"method_slug":"relu","method_name":"ReLU"},{"method_slug":"residual-block","method_name":"Residual Block"},{"method_slug":"residual-connection","method_name":"Residual Connection"},{"method_slug":"sigmoid-activation","method_name":"Sigmoid Activation"},{"method_slug":"tanh-activation","method_name":"Tanh Activation"}],"datasets_introduced":[],"methods_introduced":[],"results":[{"leaderboard":"/sota/bangla-text-detection-on-bengali-ai","task":"Bangla Text Detection","dataset":"Bengali.AI Handwritten Graphemes","model":"CycleGAN","rank_in_archive_order":1,"of":1,"metrics":{"hierarchical macro-averaged recall":"0.9762"},"uses_additional_data":false}],"syntology":{"atlas_url":null,"mcp":null,"developers":"https://syntology.ai/developers"},"arxiv_metadata":null,"syntology_extracted_results":null}