Papers with automatic AD generation

2 papers
Audio Description Generation in the Era of LLMs and VLMs: A Review of Transferable Generative AI Technologies (2025.findings-naacl)

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Challenge: Audio descriptions (ADs) are acoustic commentaries designed to assist blind and visually impaired individuals in accessing digital media content.
Approach: They examine how state-of-the-art NLP and CV technologies can be applied to generate ADs . they identify essential research directions for the future .
Outcome: The proposed technologies can be applied to generate audio descriptions (ADs) the process is time-consuming and costly, and requires significant human effort . the authors identify key research directions for the future .
What You See is What You Ask: Evaluating Audio Descriptions (2025.emnlp-main)

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Challenge: Existing studies evaluate audio descriptions (ADs) using trimmed clips, but writing them is subjective.
Approach: They propose a QA benchmark that evaluates audio descriptions at the level of short, coherent video segments.
Outcome: The proposed evaluation paradigm addresses two themes central to ADs . it compares two humannarrated AD tracks and shows that current methods lag behind human-authored ADs.

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