updates

app.py

@@ -77,11 +77,14 @@ def translate(video_file, true_caption=None):
 title = "American Sign Language Translation: An Approach Combining MoViNets and T5"
 
 description =   """
-This application surfaces a model for translation of American Sign Language (ASL). 
+This application hosts a model for translation of American Sign Language (ASL). 
 The model comprises of a fine-tuned MoViNet CNN model to generate video embeddings and a T5 encoder-decoder model 
 to generate translations from the video embeddings. This model architecture achieves a BLEU score of 1.98 
 and an average cosine similarity score of 0.21 when trained and evaluated on the YouTube-ASL dataset. 
-More information about the model training and instructions to download the models can be found in our GitHub repository <a href=https://github.com/deanna-emery/ASL-Translator>here</a>.
+More information about the model training and instructions to download the models 
+can be found in our <a href=https://github.com/deanna-emery/ASL-Translator>GitHub repository</a>.
+You can also find a overview of the project approach 
+<a href=https://www.ischool.berkeley.edu/projects/2023/signsense-american-sign-language-translation>here/a>.
 
 A limitation of this architecture is the size of the MoViNets model, making it especially slow during inference on a CPU. 
 We do not recommend uploading videos longer than 4 seconds as the video embedding generation may take some time.