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Building a Handwriting Recognition System for the New York Times Crossword | Shafik Quoraishee | TestMu 2025
Building a Handwriting Recognition System for the New York Times Crossword | Shafik Quoraishee | TestMu 2025
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About the talk
In this engaging TestMu session, 𝐒𝐡𝐚𝐟𝐢𝐤 𝐐𝐮𝐨𝐫𝐚𝐢𝐬𝐡𝐞𝐞, Senior Games Engineer, The New York Times, shares insights into the development of a handwriting recognition system for The New York Times Crossword. The project, born out of the internal Maker Week hackathon, explores the challenges and solutions behind transforming handwritten answers into a digital format. Shafik walks the audience through the journey of creating a custom handwriting recognition system using deep learning models, TensorFlow Lite, and Android-specific constraints.
The session also dives into testing challenges for machine learning systems, such as model drift, training sufficiency, and ensuring accuracy across diverse handwriting styles. Attendees gain a comprehensive understanding of the intricacies of integrating machine learning on mobile platforms while testing for real-world scenarios.
Key Takeaways:
✔ Overview of building an Android-based handwriting recognition system.
✔ Integration of machine learning models for real-time handwriting interpretation.
✔ Addressing challenges such as model drift, training data quality, and edge case recognition.
✔ Practical use of convolutional neural networks (CNNs) and TensorFlow Lite for on-device AI.
✔ Techniques for improving model accuracy with data augmentation and synthetic data.
Testμ
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