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Journal Articles International Journal on Document Analysis and Recognition Year : 2022

Combination of explicit segmentation with Seq2Seq recognition for fine analysis of children handwriting

Abstract

We consider the task of analysing children handwriting in the context of a dictation task. The objective is to detect orthographic and phonological errors. To achieve this goal, we extend an existing handwriting analysis engine, based on an explicit segmentation of the handwritten input, originally developed for children copying exercises. We present a new approach, based on the combination of this analysis engine with a deep learning word recognition approach in order to improve both the recognition and segmentation performance. Explicit segmentation needs prior knowledge, and the deep network recognition predictions are a reliable approximation of the ground truth which can guide the analysis process. We propose to combine multiple prior knowledge strategies to further improve the analysis performance. Furthermore, we exploit the deep network approximate implicit segmentation to optimise the existing analysis process in terms of complexity.
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Dates and versions

hal-03845144 , version 1 (09-11-2022)

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Omar Krichen, Simon Corbillé, Eric Anquetil, Nathalie Girard, Elisa Fromont, et al.. Combination of explicit segmentation with Seq2Seq recognition for fine analysis of children handwriting. International Journal on Document Analysis and Recognition, 2022, ⟨10.1007/s10032-022-00409-4⟩. ⟨hal-03845144⟩
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