Demo Data from SIGIR 2026 / reviewers in the wild / expert
Sheng-Wei Li
dblp:87/5247
· DBLP profile ↗
3ranked-venue papers
2as first author
1since 2021 · last 2024
0009-0002-9091-8036ORCID · reported
Domains — the database's venue-derived domains; a paper can count in several
Graphics, computer vision, multimedia, augmented reality and games · 3 · 2 first-author · 1 since 2021Artificial intelligence and machine learning · 1 · 1 first-author · 1 since 2021Computer networks · 1
Expertise — from the expertise taxonomy: the topics of the expert's papers under the CCF categories. A weight counts papers with recency: 1 for a paper about the topic, 0.3 when the topic is its context, halved every five years.
| Artificial intelligence
2 papers |
Video understanding and tracking · 99% Speech recognition and synthesis · 1% | |
| Computer graphics and multimedia
1 paper |
Multimedia analysis and retrieval · 100% |
Topics — the 6 heaviest of 8, each with the papers that count most for it
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Computer vision › Video understanding and tracking
action recognition |
0.8 | 1 | 2024 | SA-DVAE: Improving Zero-Shot Skeleton-Based Action Recognition by Disentangled Variational Autoencoders · ECCV (16) 2024 |
Computer vision › Video understanding and tracking › action recognition
skeleton-based action recognition |
0.8 | 1 | 2024 | SA-DVAE: Improving Zero-Shot Skeleton-Based Action Recognition by Disentangled Variational Autoencoders · ECCV (16) 2024 |
Computer vision › Video understanding and tracking › action recognition › action recognition under limited supervision
zero-shot action recognition |
0.8 | 1 | 2024 | SA-DVAE: Improving Zero-Shot Skeleton-Based Action Recognition by Disentangled Variational Autoencoders · ECCV (16) 2024 |
Multimedia analysis and retrieval › multimedia analysis › cross-media analysis
cross-media correlation |
0.1 | 1 | 2005 | How speech/text alignment benefits web-based learning · ACM Multimedia 2005 |
Learning and educational technologies
language learning |
0.1 | 1 | 2005 | How speech/text alignment benefits web-based learning · ACM Multimedia 2005 |
Natural language and speech › Speech recognition and synthesis
speech-text alignment |
0.0 | 1 | 2005 | How speech/text alignment benefits web-based learning · ACM Multimedia 2005 |
Methods — techniques the papers use, named apart from their topics
variational autoencoder · 0.8disentangled representation learning · 0.8synchronization · 0.2cross-media correlation · 0.2
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2024 | SA-DVAE: Improving Zero-Shot Skeleton-Based Action Recognition by Disentangled Variational Autoencoders
Sheng-Wei Li, Zi-Xiang Wei, Yi-Hsin Yu, Chih-Yuan Yang, Yung-Jen Hsu 0001 |
ECCV (16) | 1 |
| 2007 | Exploring many-to-one speech-to-text correlation for web-based language learningabstractThis article investigates the correlations between multimedia objects (particularly speech and text) involved in language lectures in order to design an effective presentation mechanism for web-based learning. The cross-media correlations are classified into implicit relations (retrieved by computing) and explicit relations (recorded during the preprocessing stage). The implicit temporal correlation between speech and text is primarily to help to negotiate supplementary lecture navigations like tele-pointer movement, lips-sync movement, and content scrolling. We propose a speech-text alignment framework, using an iterative algorithm based on local alignment, to probe many-to-one temporal correlations, and not the one-to-one only. The proposed framework is a more practical method for analyzing general language lectures, and the algorithm's time complexity conforms to the best-possible computation cost, O(nm) , without introducing additional computation. In addition, we have shown the feasibility of creating vivid presentations by exploiting implicit relations and artificially simulating some explicit media. To facilitate the navigation of integrated multimedia documents, we develop several visualization techniques for describing media correlations, including guidelines for speech-text correlations, visible-automatic scrolling, and levels of detail of timeline, to provide intuitive and easy-to-use random access mechanisms. We evaluated the performance of the analysis method and human perceptions of the synchronized presentation. The overall performance of the analysis method is that about 99.5% of the words analyzed are of a temporal error within 0.5 sec and the subjective evaluation result shows that the synchronized presentation is highly acceptable to human beings. Herng-Yow Chen, Sheng-Wei Li |
ACM Trans. Multim. Comput. Commun. Appl. | 2 |
| 2005 | How speech/text alignment benefits web-based learningabstractThis demonstration presents an integrated web-based synchronized scenario for many-to-one cross-media correlations between speech (an EFL, English as Foreign Language, lecture with free-style lecturing behaviors) and the corresponding textual content. The analysis/presentation of the temporal correlations enable the vivid web-based language learning through the interactive functions: browsing speech via content, word-by-word pointer guidance, synchronized scrolling/highlighting, and listening training mode. We regularly analyze and repackage the multimedia content of VoA (Voice of America) [1], ICRT (International Community Radio Taipei) [2], and Online Lectures in our University [3]. Through the subjective experiments, this repackaged synchronized speech/text content does facilitate the learning for EFL learners. Sheng-Wei Li, Hao-Tung Lin, Herng-Yow Chen |
ACM Multimedia | 1 |