SOURCE-LINKED INTELLIGENCE
Low-Latency Spell Correction for Japanese Music Search Queries
Spell correction for Japanese search queries presents unique challenges due to the co-existence of four writing scripts (Latin/romaji, hiragana, katakana, and kanji) and the distinct error patterns each script induces. We present a compact BART-based sequence-to-sequence model (3 encoder + 3 decoder layers) designed for low-latency spell correction of Japanese music search queries. The core contribution lies in a script-aware synthetic misspelling generation pipeline that produces realistic training data by combining keyboard-layout models (QWERTY and flick input), phonetic confusion priors mi
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Evidence & attribution
- arXiv · AI, language, vision and robotics · 2026-09-02T12:30:08.000Z
First collected: 2026-09-21T05:32:15.665Z. This is not the publication date.