Summary of Leveraging Speech For Gesture Detection in Multimodal Communication, by Esam Ghaleb et al.
Leveraging Speech for Gesture Detection in Multimodal Communication
by Esam Ghaleb, Ilya Burenko, Marlou Rasenberg, Wim Pouw, Ivan Toni, Peter Uhrig, Anna Wilson, Judith Holler, Aslı Özyürek, Raquel Fernández
First submitted to arxiv on: 23 Apr 2024
Categories
- Main: Computer Vision and Pattern Recognition (cs.CV)
- Secondary: Artificial Intelligence (cs.AI)
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| Summary difficulty | Written by | Summary |
|---|---|---|
| High | Paper authors | High Difficulty Summary Read the original abstract here |
| Medium | GrooveSquid.com (original content) | Medium Difficulty Summary A novel approach to detecting co-speech hand gestures is presented in this research paper. The authors address three key challenges: gesture variability, temporal misalignment between speech and gestures, and differences in sampling rates between modalities. To overcome these challenges, they employ separate backbone models for each modality, utilize extended speech time windows, and integrate visual and speech information using Transformer encoders and early fusion techniques. The results show that combining multimodal information significantly enhances gesture detection performance, outperforming unimodal and late fusion methods. Additionally, the study finds a correlation between gesture prediction confidence and low-level speech frequency features potentially associated with gestures. |
| Low | GrooveSquid.com (original content) | Low Difficulty Summary This research paper explores how to detect hand gestures that happen at the same time as people are talking. The authors want to make sure their method can handle different types of gestures, the timing of when the gesture starts and ends, and how the information from vision and hearing is combined. They use special models for each type of information, take a longer look at what’s being said, and combine the visual and audio signals using a new technique. The results show that combining all this information makes it easier to detect gestures correctly. |
Keywords
» Artificial intelligence » Transformer
