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Benchmarking multilingual ASR across noisy media
How engine selection shifts word error rate across language pairs and audio conditions.
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FELTIV LABS
How engine selection shifts word error rate across language pairs and audio conditions.
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Measuring whether segment-level confidence predicts where human edits actually land.
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Listener study comparing diarized multi-voice dubs against single-voice baselines.
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Socials & Events
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3d · LinkedIn
We're at Localization World next month — come talk routing, QC, and where AI actually earns its place.
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1w · LinkedIn
New benchmark round: 12 engines, 40 language pairs, one very long spreadsheet. Results soon.
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2w · LinkedIn
Our team on why confidence scoring changed how localization reviews get staffed.