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Journals / Çeviribilim ve Uygulamaları Dergisi / 2025 / Sayı: 39

Comparing Human and AI-Generated Museum Audio Descriptions: A Corpus-Based Linguistic Analysis

Müze Sesli Betimlemelerinde İnsan ve Yapay Zekâ Üretimlerinin Karşılaştırılması: Derlem Temelli Bir Çalışma

Tules Önenç(Hacettepe Univeristesi)0000-0003-2275-7111
A. Şirin Okyayuz(Hacettepe Üniveristesi)0000-0001-7512-2764
Pages
154–173
Publication Date
2025-12-31
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AI Summary & Key Takeaways

AI Insight
⚡ TL;DR(Too Long; Didn't Read)

The results of the analysis indicate that, while human-authored texts remain the gold standard for the time being, AI-based automatic description systems have significant potential to meet accessibility standards and facilitate the development of inclusive, semantically robust automatic description tools.

📌 3 Key Takeaways

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Objective & Hypothesis:Audio description (AD) in cultural heritage settings serves as an accessibility service that enables blind and partially-sighted visitors to interact with the diverse visual content in museums and galleries.
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Key Findings & Data:With the growing need to provide enabling services for a broader audience in audio-visual media, the implementation of artificial intelligence (AI) tools has become significant in cultural heritage contexts as well.
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Conclusion & Impact:The results of the analysis indicate that, while human-authored texts remain the gold standard for the time being, AI-based automatic description systems have significant potential to meet accessibility standards and facilitate the development of inclusive, semantically robust automatic description tools.
🔬Design:Modeling & Simulation
📍Scope:Comprehensive Sample
⚙️Variables:sesli betimleme · müze erişilebilirliği · üretken yapay zeka

Abstract

Audio description (AD) in cultural heritage settings serves as an accessibility service that enables blind and partially-sighted visitors to interact with the diverse visual content in museums and galleries. With the growing need to provide enabling services for a broader audience in audio-visual media, the implementation of artificial intelligence (AI) tools has become significant in cultural heritage contexts as well. In this context, the current study evaluates the applicability of Large Language Models (LLMs) and artificial intelligence (AI) tools through generating ADs of selected static artworks. It does so by implementing a corpus based linguistic analysis of AD texts that are produced by three modalities: (1) a Human-Authored AD Corpus; which consists of AD texts written by experts, (2) a Baseline AI AD Corpus which is a compilation of texts that an untrained AI model generates, and (3) a Trained AI AD Corpus in which AD texts are generated through an AI model that is specifically trained with domain-specific datasets. The results of the corpus analysis are presented and discussed within the framework of adherence to the characteristics of museum AD. As part of a vast doctoral research project, this study is the first attempt to investigate the linguistic attributes of Turkish museum AD and to train an AI model to generate AD texts for static artworks. The results of the analysis indicate that, while human-authored texts remain the gold standard for the time being, AI-based automatic description systems have significant potential to meet accessibility standards and facilitate the development of inclusive, semantically robust automatic description tools.

Özet

Kültürel miras alanlarında sesli betimleme (SB), görme engelli ve az gören ziyaretçilerin müzelerdeki ve galerilerdeki çeşitli görsel içerikle etkileşim kurmasını sağlayan bir erişilebilirlik hizmetidir. Görsel-işitsel medyada daha geniş bir kitleye yönelik etkinleştirici hizmetler sunma ihtiyacının artmasıyla birlikte, yapay zekâ (YZ) araçlarının uygulanması kültürel miras bağlamlarında da giderek artmaktadır. Bu bağlamda, mevcut çalışma, seçilen durağan sanat eserlerinin sesli betimleme metinlerini oluşturarak YZ modellerinin ve araçlarının uygulanabilirliğini değerlendirmektedir. Bunu, üç yöntemle üretilen SB metninin derleme tabanlı dilbilimsel bir analizini uygulayarak yapmaktadır: (1) Uzmanlar tarafından yazılan SB metinlerinden oluşan İnsan Yazarlı SB Derlemi, (2) Eğitimsiz bir YZ modelinin oluşturduğu metinlerin bir derlemesi olan Temel YZ SB Derlemi ve (3) Etki alanına özel veri kümeleriyle eğitilmiş bir YZ modeli aracılığıyla oluşturulan SB metinlerinin bulunduğu Eğitimli YZ SB Derlemi. Derlem analizinin sonuçları, müze SB'sinin özelliklerine uygunluk çerçevesinde sunulmakta ve tartışılmaktadır. Bir doktora araştırmasının bir parçası olan bu çalışma, Türkçe müze SB'sinin dilbilimsel özelliklerini araştırmaya ve özellikle durağan sanat eserleri için SB metinleri üreten bir YZ modelini eğitmeye yönelik ilk girişimdir. Analizin sonuçları, insan tarafından yazılan metinler şimdilik altın standart olmaya devam etse de özelleştirilmiş veri setleriyle eğitilen YZ tabanlı otomatik betimleme sistemlerinin erişilebilirlik standartlarına uyum ve kapsayıcılık açısından güçlü betimleme araçlarının geliştirilmesini kolaylaştırma konusunda önemli bir potansiyele sahip olduğunu göstermektedir.

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Cite This Article

Önenç, T., Okyayuz, A. Ş. (2025). Comparing Human and AI-Generated Museum Audio Descriptions: A Corpus-Based Linguistic Analysis. Çeviribilim ve Uygulamaları Dergisi, Sayı: 39, 154–173. https://doi.org/10.37599/ceviri.1791606

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