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ASR models evaluated for Italian TV subtitling, showing human-in-the-loop necessity

By PulseAugur Editorial · [1 sources] ·

A new research paper evaluates the performance of four state-of-the-art Automatic Speech Recognition (ASR) models—Whisper Large v2, AssemblyAI Universal, Parakeet TDT v3 0.6b, and WhisperX—in the context of subtitling Italian television programs. The study, conducted on a 50-hour dataset, found that while these models cannot yet achieve full autonomy for professional subtitling, they significantly enhance human productivity. The researchers propose a human-in-the-loop approach supported by a cloud-based infrastructure. AI

IMPACT ASR models show potential to boost human subtitling productivity but require human oversight for professional quality.

RANK_REASON The cluster is a research paper evaluating existing models on a specific task. [lever_c_demoted from research: ic=1 ai=1.0]

Read on arXiv cs.CL →

AI-generated summary · Google Gemini · from 1 sources. How we write summaries →

ASR models evaluated for Italian TV subtitling, showing human-in-the-loop necessity

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The cluster is a research paper evaluating existing models on a specific task. [lever_c_demoted from research: ic=1 ai=1.0]
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COVERAGE [1]

  1. arXiv cs.CL TIER_1 English(EN) · Alessandro Lucca, Francesco Corso, Francesco Pierri ·

    From Speech to Subtitles: Evaluating ASR Models in Subtitling Italian Television Programs

    arXiv:2512.19161v2 Announce Type: replace Abstract: Subtitles are essential for video accessibility and audience engagement. Modern Automatic Speech Recognition (ASR) systems, built upon Encoder-Decoder neural network architectures and trained on massive amounts of data, have pro…

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