Add SEDA (Tan et al., 2024) to Video-to-Text section

src/index.md

@@ -802,6 +802,8 @@ SSVP-SLT achieves state-of-the-art performance on How2Sign [@dataset:duarte2020h
 They conclude that SLT models can be pretrained in a privacy-aware manner without sacrificing too much performance.
 Additionally, the authors release DailyMoth-70h, a new 70-hour ASL dataset from [The Daily Moth](https://www.dailymoth.com/).
 
+@tan-etal-2024-seda extend this sign language transformer with SEDA, a data augmentation framework that augments sign features through multiple sign embeddings and augments spoken text via lemmatization, achieving competitive WER, BLEU, and ROUGE on RWTH-PHOENIX-Weather-2014T.
+
 #### Text-to-Video
 Text-to-Video, also known as sign language production, is the task of producing a video that adequately represents
 a spoken language text in sign language.

src/references.bib

@@ -4782,6 +4782,14 @@ @inproceedings{dataset:reverdy-etal-2024-stk
     author = "Reverdy, Cl{\'e}ment  and
       Gibet, Sylvie  and
       Le Naour, Thibaut",
+}
+
+@inproceedings{tan-etal-2024-seda,
+    title = "{SEDA}: Simple and Effective Data Augmentation for Sign Language Understanding",
+    author = "Tan, Sihan  and
+      Miyazaki, Taro  and
+      Itoyama, Katsutoshi  and
+      Nakadai, Kazuhiro",
     editor = "Efthimiou, Eleni  and
       Fotinea, Stavroula-Evita  and
       Hanke, Thomas  and
@@ -4816,3 +4824,7 @@ @inproceedings{dataset:reverdy-etal-2024-stk
     url = "https://aclanthology.org/2024.signlang-1.35/",
     pages = "315--322"
 }
+
+    url = "https://aclanthology.org/2024.signlang-1.41/",
+    pages = "370--375"
+}