Fine-tuning M2M100 on 9,000 parallel examples yields a Singlish-to-Sinhala transliterator that strongly outperforms a rule-based baseline on held-out shared-task test sets.
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Sinhala Transliteration: A Comparative Analysis Between Rule-based and Seq2Seq Approaches
Fine-tuning M2M100 on 9,000 parallel examples yields a Singlish-to-Sinhala transliterator that strongly outperforms a rule-based baseline on held-out shared-task test sets.