Cite Susman & Kimmelman 2024: CNN+rule-based eye blink detection in LSF

src/index.md

@@ -1175,6 +1175,7 @@ Therefore, data collection often requires significant efforts and costs of on-si
 
 ###### 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.
+Targeting prosodic non-manual annotation specifically, @susman-kimmelman-2024-eye trained a CNN classifier of eye openness (open, in-between, closed) on French Sign Language data and combined it with rule-based temporal aggregation to detect linguistically defined eye blinks, outperforming an Eye Aspect Ratio (EAR) baseline computed from MediaPipe landmarks.
 
 ### Practice Deaf Collaboration
 

src/references.bib

@@ -4496,3 +4496,22 @@ @inproceedings{rathmann-etal-2024-visuolab
  url = {https://aclanthology.org/2024.signlang-1.32},
  year = {2024}
 }
+
+@inproceedings{susman-kimmelman-2024-eye,
+    title = "Eye Blink Detection in Sign Language Data Using {CNN}s and Rule-Based Methods",
+    author = "Susman, Margaux  and
+      Kimmelman, Vadim",
+    editor = "Efthimiou, Eleni  and
+      Fotinea, Stavroula-Evita  and
+      Hanke, Thomas  and
+      Hochgesang, Julie A.  and
+      Mesch, Johanna  and
+      Schulder, Marc",
+    booktitle = "Proceedings of the LREC-COLING 2024 11th Workshop on the Representation and Processing of Sign Languages: Evaluation of Sign Language Resources",
+    month = may,
+    year = "2024",
+    address = "Torino, Italia",
+    publisher = "ELRA and ICCL",
+    url = "https://aclanthology.org/2024.signlang-1.40/",
+    pages = "361--369"
+}