arXiv — NLP / Computation & Language · · 3 min read

Towards Digital Preservation of Efik: TTS for a Low-Resource African Language

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Computer Science > Computation and Language

arXiv:2607.04515 (cs)
[Submitted on 5 Jul 2026]

Title:Towards Digital Preservation of Efik: TTS for a Low-Resource African Language

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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.
Comments: 6 pages, 2 figures. Accepted to Interspeech 2026
Subjects: Computation and Language (cs.CL)
Cite as: arXiv:2607.04515 [cs.CL]
  (or arXiv:2607.04515v1 [cs.CL] for this version)
  https://doi.org/10.48550/arXiv.2607.04515
arXiv-issued DOI via DataCite (pending registration)

Submission history

From: Offiong Bassey Edet [view email]
[v1] Sun, 5 Jul 2026 21:37:15 UTC (91 KB)
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