{"ID":5937809,"CreatedAt":"2026-07-07T03:14:33.014478982Z","UpdatedAt":"2026-07-08T21:35:32.327944328Z","DeletedAt":null,"paper_url":"https://arxiv.org/abs/2607.04515","arxiv_id":"2607.04515","title":"Towards Digital Preservation of Efik: TTS for a Low-Resource African Language","abstract":"Efik, a tonal language spoken by about 3 million second language speakers and 1.5 million native speakers in Southeastern Nigeria, remains underrepresented in speech synthesis research. We present the first documented end-to-end text-to-speech study for Efik, introducing a curated single speaker corpus of 2,632 utterances totaling three hours and a comparative evaluation of four neural models (VITS, MMS-TTS, SpeechT5, and Orpheus-TTS) under low resource conditions. Native speakers evaluated the systems using MOS, Nat-MOS, and A-MOS. MMS-TTS achieved the highest MOS of 3.80 +/- 0.63 and produced more stable long form speech, though tonal errors persisted. Other models showed greater tonal and prosodic inconsistencies. These results provide a reproducible baseline and highlight the need for larger corpora and tone aware modeling for tonal African languages.","short_abstract":"Efik, a tonal language spoken by about 3 million second language speakers and 1.5 million native speakers in Southeastern Nigeria, remains underrepresented in speech synthesis research. We present the first documented end-to-end text-to-speech study for Efik, introducing a curated single speaker corpus of 2,632 utteran...","url_abs":"https://arxiv.org/abs/2607.04515","url_pdf":"https://arxiv.org/pdf/2607.04515v1","authors":"[\"Offiong Bassey Edet\",\"Emmanuel Oyo-Ita\",\"Archibong Okon Archibong\",\"David Effanga Bassey\",\"Mbuotidem Sunday Awak\"]","published":"2026-07-05T21:37:15Z","proceeding":"cs.CL","tasks":"[\"cs.CL\"]","methods":"[]","has_code":false}