MELD: A Multimodal Multi-Party Dataset for Emotion Recognition in Conversation
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Updated
Mar 10, 2024 - Python
MELD: A Multimodal Multi-Party Dataset for Emotion Recognition in Conversation
This repository contains various models targetting multimodal representation learning, multimodal fusion for downstream tasks such as multimodal sentiment analysis.
Platform for Situated Intelligence
Multimodal Sarcasm Detection Dataset
A comprehensive reading list for Emotion Recognition in Conversations
Context-Dependent Sentiment Analysis in User-Generated Videos
Mobile application for exploring fitness data using both speech and touch interaction.
Multimodal sentiment analysis using hierarchical fusion with context modeling
Unsupervised Multimodal Clustering for Semantics Discovery in Multimodal Utterances (ACL 2024)
Companion Repo for the Vision Language Modelling YouTube series - https://bit.ly/3PsbsC2 - by Prithivi Da. Open to PRs and collaborations
Using voice and pen to draw diagrams quickly with automatically suggested icons and texts by AI in talking.
A multimodal face liveness detection module that can be used in the context of face anti-spoofing
Technical Draft: A platform to augment web applications with multimodal interactions
Code for ICMI2020 and ICMI2021 papers: "Studying Person-Specific Pointing and Gaze Behavior for Multimodal Referencing of Outside Objects from a Moving Vehicle" and "ML-PersRef: A Machine Learning-based Personalized Multimodal Fusion Approach for Referencing Outside Objects From a Moving Vehicle"
Project for Multimodal Interaction course (A.Y. 2019/2020), GesturePad
Multimodal AI Assistant with Google Gemini-1.5-pro, gTTS, PIL, and SpeechRecognition Technologies!
Repository to contain MMI development during UTA CSE REU 2019. Makes use of Open-Myo, a module to get data from a Myo armband using a generic BLE interface.
Control of some Spotify's functionalities by voice
Challenge of gesture recognition for the course : "Multimodal Processing Recognition and Interaction" of the HES-SO university (Switzerland)
Developed a multimodal interactive quiz app allowing users to select answers via hand gestures. Created a user-friendly UI/UX in Figma and built the front end with React Native, using MongoDB for data management. Implemented a backend with Express and Node.js, and trained CNN models in Python for gesture recognition, enhancing user engagement.
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