5 papers
Segment, Embed, and Align: A Universal Recipe for Aligning Subtitles to Signing
Zifan Jiang, Youngjoon Jang, Liliane Momeni +3
The goal of this work is to develop a universal approach for aligning subtitles (i.e., spoken language text with corresponding timestamps) to continuous sign language videos. Prior…
Lost in Translation, Found in Embeddings: Sign Language Translation and Alignment
Youngjoon Jang, Liliane Momeni, Zifan Jiang +3
Our aim is to develop a unified model for sign language understanding, that performs sign language translation (SLT) and sign-subtitle alignment (SSA). Together, these two tasks en…
More than a Moment: Towards Coherent Sequences of Audio Descriptions
Eshika Khandelwal, Junyu Xie, Tengda Han +5
Audio Descriptions (ADs) convey essential on-screen information, allowing visually impaired audiences to follow videos. To be effective, ADs must form a coherent sequence that help…
Shot-by-Shot: Film-Grammar-Aware Training-Free Audio Description Generation
Junyu Xie, Tengda Han, Max Bain +5
Our objective is the automatic generation of Audio Descriptions (ADs) for edited video material, such as movies and TV series. To achieve this, we propose a two-stage framework tha…
Lost in Translation, Found in Context: Sign Language Translation with Contextual Cues
Youngjoon Jang, Haran Raajesh, Liliane Momeni +2
Our objective is to translate continuous sign language into spoken language text. Inspired by the way human interpreters rely on context for accurate translation, we incorporate ad…