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Abstract
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The field of translation is undergoing a significant shift due to technological advancements and growing legal and social demands for accessibility. Audio description (AD), developed to make audiovisual content accessible to individuals with visual impairments, exemplifies this change. With legislation requiring full accessibility by 2025, a shortage of trained audio describers presents a challenge. One proposed solution is applying machine translation (MT) to render ADs in multiple languages. Given AD's concise and concrete style, it is well-suited to MT applications (Vercauteren et al., 2021).
Language technologies have significantly influenced Translation Studies, particularly in digital and audiovisual media. Since the early 2000s, MT has transformed translation practices, shifting perceptions from a threat to one of collaboration (Bywood et al., 2017; O'Hagan, 2019, 2020). The current focus is no longer on whether to use MT, but on how best to integrate it into workflows to improve quality and efficiency (O'Hagan, 2019, 2020).
AD also contributes to cultural inclusion. Jankowska (2024) highlights the use of pivot templates in AD workflows to enrich cultural relevance, resulting in more context-sensitive and inclusive narratives. This approach fosters greater cross-cultural understanding and reflects diverse experiences in media content.
Beyond accessibility, AD raises awareness of the social responsibilities of media creators. Aligned with the principles of universal design, it promotes inclusive practices that benefit a broad audience regardless of ability. Such efforts contribute to a more equitable media environment and support continued dialogue on representation and accessibility. (Hardman et al., 2008).
The translation of audio descriptions (ADs), whether human- or machine-generated, plays a crucial role in enhancing multimedia accessibility for visually impaired audiences. AD transforms visual content into verbal narration, enabling those with visual imp
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