Phonetic Completeness Over Prosodic Diversity: Syllable-Level Synthetic Corpus Construction for Low-Resource Penang Hokkien Speech Synthesis

This study presents the first Text-to-Speech (TTS) model for Penang Hokkien, a low-resource tonal dialect at risk of extinction. To address phonological sparsity in the collected speech corpus, we propose a two-stage fine-tuning approach that emphasizes comprehensive phonetic coverage through syllable-level synthetic augmentation while subsequently refining prosodic naturalness using real speech recordings. By supplementing a limited 45-minute real speech corpus with a 2-hour syllable-level concatenative synthetic corpus, the full dialectal inventory of approximately 2,000 unique syllable-tone combinations was encompassed. Experimental results suggest that improving syllable-tone coverage contributes substantially to intelligibility and tonal accuracy in this low-resource tonal setting. Technical optimizations, including a 600-ms cross-fading technique to mitigate boundary artifacts and numerical tone markers to reduce token sparsity, further improved model stability and synthesis quality. The final model achieved a Mean Opinion Score (MOS) of 3.92.

@article{Lai2026,
  title     = {Phonetic Completeness Over Prosodic Diversity: Syllable-Level Synthetic Corpus Construction for Low-Resource Penang Hokkien Speech Synthesis},
  journal   = {International Journal of Advanced Computer Science and Applications},
  volume    = {17},
  number    = {5},
  year      = {2026},
  publisher = {The Science and Information Organization},
  author    = {Yu Liang Lai and Yen Min Jasmina Khaw and Seng Poh Lim and Tien Ping Tan},
  doi       = {10.14569/IJACSA.2026.0170563},
  url       = {https://doi.org/10.14569/IJACSA.2026.0170563}
}