ReNikud: Audio-Supervised Hebrew Grapheme-to-Phoneme Conversion
ReNikud addresses Hebrew G2P challenges by using weak audio supervision to create pronunciation models for text-to-speech. It develops a pseudo-vocalization architecture that forces each Hebrew letter to predict a phonetic triplet (consonant, vowel, stress). This method outperforms baselines on complex, colloquial speech benchmarks like MILIM.