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Fast Multi-language LSTM-based Online Handwriting Recognition

arXiv 1902.10525 ↗First posted 22 Feb 2019cs.CL cs.LG stat.MLcited by 22

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Abstract (arXiv)

We describe an online handwriting system that is able to support 102 languages using a deep neural network architecture. This new system has completely replaced our previous Segment-and-Decode-based system and reduced the error rate by 20%-40% relative for most languages. Further, we report new state-of-the-art results on IAM-OnDB for both the open and closed dataset setting. The system combines methods from sequence recognition with a new input encoding using B'ezier curves. This leads to up to 10x faster recognition times compared to our previous system. Through a series of experiments we determine the optimal configuration of our models and report the results of our setup on a number of additional public datasets.

Key facts. Cited by 22 papers in the map (data through 14 Oct 2026). First posted on arXiv 22 Feb 2019.

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Citing papers per year: 2021: 7; 2022: 2; 2023: 6; 2024: 2; 2025: 3; 2026: 2.

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  1. 2021Vectorization and Rasterization: Self-Supervised Learning for Sketch and Handwritingcited by 38
  2. 2024MathWriting: A Dataset For Handwritten Mathematical Expression Recognitioncited by 21
  3. 2022Benchmarking Online Sequence-to-Sequence and Character-based Handwriting Recognition from IMU-Enhanced Penscited by 13
  4. 2021Recognizing Vector Graphics without Rasterizationcited by 11
  5. 2024Representing Online Handwriting for Recognition in Large Vision-Language Modelscited by 7
  6. 2022Auxiliary Cross-Modal Representation Learning with Triplet Loss Functions for Online Handwriting Recognitioncited by 6
  7. 2021An Automatic System to Monitor the Physical Distance and Face Mask Wearing of Construction Workers in COVID-19 Pandemiccited by 5
  8. 2021Towards an IMU-based Pen Online Handwriting Recognizercited by 5
  9. 2023Transformers versus LSTMs for electronic tradingcited by 4
  10. 2021TRACE: A Differentiable Approach to Line-level Stroke Recovery for Offline Handwritten Textcited by 3
  11. 2023Character Queries: A Transformer-based Approach to On-Line Handwritten Character Segmentationcited by 3
  12. 2023Self-Supervised Representation Learning for Online Handwriting Text Classificationcited by 2
10 more
  1. 2023DSS: Synthesizing long Digital Ink using Data augmentation, Style encoding and Split generationcited by 2
  2. 2025InkFM: A Foundational Model for Full-Page Online Handwritten Note Understandingcited by 2
  3. 2021Writing in The Air: Unconstrained Text Recognition from Finger Movement Using Spatio-Temporal Convolutioncited by 1
  4. 2021Data Incubation -- Synthesizing Missing Data for Handwriting Recognitioncited by 1
  5. 2023LiteLSTM Architecture Based on Weights Sharing for Recurrent Neural Networkscited by 1
  6. 2023Sampling and Ranking for Digital Ink Generation on a tight computational budgetcited by 0
  7. 2025Robust and Efficient Writer-Independent IMU-Based Handwriting Recognitioncited by 0
  8. 2025Preserving Privacy Without Compromising Accuracy: Machine Unlearning for Handwritten Text Recognitioncited by 0
  9. 2026ScribeTokens: Fixed-Vocabulary Tokenization of Digital Inkcited by 0
  10. 2026Tokenization vs. Augmentation: A Systematic Study of Writer Variance in IMU-Based Online Handwriting Recognitioncited by 0