Add Lascar et al. 2024 on LSF annotation without pre-existing dictionary#139
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AmitMY
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Apr 28, 2026
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| ###### Automating Annotation {-} | ||
| One helpful research direction for collecting more data that enables the development of deployable SLP models is creating tools that can simplify or automate parts of the collection and annotation process. One of the most significant bottlenecks in obtaining more adequate signed language data is the time and scarcity of experts required to perform annotation. Therefore, tools that perform automatic parsing, detection of frame boundaries, extraction of articulatory features, suggestions for lexical annotations, and allow parts of the annotation process to be crowdsourced to non-experts, to name a few, have a high potential to facilitate and accelerate the availability of good data. | ||
| @lascar-etal-2024-annotation extend this line of work to French Sign Language by building a bilingual LSF/French lexicon from the subtitled Mediapi-RGB corpus without any pre-existing dictionary, combining weakly-supervised sign spotting with expert review and a supervised MLP classifier on Video Swin Transformer features to automatically annotate lexical units in continuous video. |
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this is in a section about recommendations, we should include it in dataset papers
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Done — moved to Dataset Papers. |
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Extends the Automating Annotation discussion with a French Sign Language case where a bilingual lexicon is built from a subtitled corpus via weakly-supervised sign spotting plus expert review, then used to train a supervised classifier for lexical-unit annotation. Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
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src/references.bib.Test plan
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