From 0cb7db66764df9c4b5af980f39fd45d05228449e Mon Sep 17 00:00:00 2001 From: github-actions Date: Tue, 10 Sep 2024 18:53:14 +0000 Subject: [PATCH] Daily build by GitHub Actions --- .../E18/Personalized-Multimodal-Emotion-Prediction/index.json | 2 +- projects/v1/4yp/E18/index.json | 2 +- projects/v1/all/index.json | 2 +- 3 files changed, 3 insertions(+), 3 deletions(-) diff --git a/projects/v1/4yp/E18/Personalized-Multimodal-Emotion-Prediction/index.json b/projects/v1/4yp/E18/Personalized-Multimodal-Emotion-Prediction/index.json index f5aae549..a30cbf7d 100644 --- a/projects/v1/4yp/E18/Personalized-Multimodal-Emotion-Prediction/index.json +++ b/projects/v1/4yp/E18/Personalized-Multimodal-Emotion-Prediction/index.json @@ -1,6 +1,6 @@ { "title": "Personalized Multimodal Emotion Prediction", - "description": "Our aim is to build an ensemble model that is based on reinforcement learning, and capable of capturing the user specific weight of each modality (visual,audio,text) in the emotional status.", + "description": "In this research, we introduce a personalized emotion prediction model that focuses on four key emotions: happy, sad, neutral, and angry. What makes this model special is its ability to adapt to each individual user, learning from how they personally express emotions and adjusting the importance of each modality accordingly.", "category": { "title": "Undergraduate Research Projects", "code": "4yp", diff --git a/projects/v1/4yp/E18/index.json b/projects/v1/4yp/E18/index.json index 5d62d7fc..fc212a4e 100644 --- a/projects/v1/4yp/E18/index.json +++ b/projects/v1/4yp/E18/index.json @@ -170,7 +170,7 @@ }, "e18-4yp-Personalized-Multimodal-Emotion-Prediction": { "title": "Personalized Multimodal Emotion Prediction", - "description": "Our aim is to build an ensemble model that is based on reinforcement learning, and capable of capturing the user specific weight of each modality (visual,audio,text) in the emotional status.", + "description": "In this research, we introduce a personalized emotion prediction model that focuses on four key emotions: happy, sad, neutral, and angry. What makes this model special is its ability to adapt to each individual user, learning from how they personally express emotions and adjusting the importance of each modality accordingly.", "category": { "title": "Undergraduate Research Projects", "code": "4yp", diff --git a/projects/v1/all/index.json b/projects/v1/all/index.json index 91b69f36..c8a9d4a8 100644 --- a/projects/v1/all/index.json +++ b/projects/v1/all/index.json @@ -20057,7 +20057,7 @@ }, "e18-4yp-Personalized-Multimodal-Emotion-Prediction": { "title": "Personalized Multimodal Emotion Prediction", - "description": "Our aim is to build an ensemble model that is based on reinforcement learning, and capable of capturing the user specific weight of each modality (visual,audio,text) in the emotional status.", + "description": "In this research, we introduce a personalized emotion prediction model that focuses on four key emotions: happy, sad, neutral, and angry. What makes this model special is its ability to adapt to each individual user, learning from how they personally express emotions and adjusting the importance of each modality accordingly.", "category": { "title": "Undergraduate Research Projects", "code": "4yp",