Summary of A Permuted Autoregressive Approach to Word-level Recognition For Urdu Digital Text, by Ahmed Mustafa et al.
A Permuted Autoregressive Approach to Word-Level Recognition for Urdu Digital Text
by Ahmed Mustafa, Muhammad Tahir Rafique, Muhammad Ijlal Baig, Hasan Sajid, Muhammad Jawad Khan, Karam Dad Kallu
First submitted to arxiv on: 27 Aug 2024
Categories
- Main: Computer Vision and Pattern Recognition (cs.CV)
- Secondary: Artificial Intelligence (cs.AI)
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| Summary difficulty | Written by | Summary |
|---|---|---|
| High | Paper authors | High Difficulty Summary Read the original abstract here |
| Medium | GrooveSquid.com (original content) | Medium Difficulty Summary A novel word-level Optical Character Recognition (OCR) model is introduced for digital Urdu text, utilizing transformer-based architectures and attention mechanisms. The model addresses distinct challenges of Urdu script recognition through a permuted autoregressive sequence (PARSeq) architecture, enabling context-aware inference and iterative refinement. This approach effectively manages character reordering and overlapping characters commonly encountered in Urdu script. Trained on approximately 160,000 Urdu text images, the model demonstrates high accuracy in capturing intricacies of Urdu script, achieving a Character Error Rate (CER) of 0.178. Despite ongoing challenges, the model exhibits superior accuracy and effectiveness in practical applications. |
| Low | GrooveSquid.com (original content) | Low Difficulty Summary This research paper is about a new way to recognize words from digital texts written in Urdu. The method uses special computer architectures and attention mechanisms to solve some unique problems with recognizing Urdu text. The approach helps the computer understand context and make better guesses when characters are jumbled or overlapping, which often happens in Urdu writing. After being trained on many examples of Urdu text, this method is very good at reading Urdu words correctly. It might not be perfect yet, but it’s a big step forward in recognizing Urdu text. |
Keywords
» Artificial intelligence » Attention » Autoregressive » Cer » Inference » Transformer
