SOURCE-LINKED INTELLIGENCE
Orukeet: Multilingual ASR with Frozen Gabor Kernels
Orukeet replaces half of an adapted Parakeet encoder's temporal filters with 12,288 fitted Gabor kernels, freezes these replacements, and trains the remaining parameters on multilingual and multi-accent data. Final adaptation and checkpoint selection use LibriSpeech test-other. Across 20,146 FLEURS recordings in 25 languages, pooled word error rate (WER) falls from Parakeet's 11.01% to Orukeet's 9.85%, a 10.6% relative reduction. Orukeet has lower WER on 23 of the 25 languages. Orukeet outperforms Parakeet on 61 out of 74 tested splits, including LibriSpeech test-clean (1.46% vs. 1.53% WER), t
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Evidence & attribution
- arXiv · AI, language, vision and robotics · 2026-09-09T11:30:03.000Z
First collected: 2026-09-20T19:32:24.350Z. This is not the publication date.