Contributing to Speech-to-Speech Translation for African Low-Resource Languages : Study of French-Mooré Pair

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Résumé

Most of African low-resource languages are primarily spoken rather than written and lack large, standardized textual resources. In many communities, low literacy rates and limited access to formal education mean that text-based translation technologies alone are insufficient for effective communication. As a result, speech-to-speech translation systems play a crucial role by enabling direct and natural interaction across languages without requiring reading or writing skills. Such systems are essential for improving access to information, public services, healthcare, and education. The goal of our work is to build powerful transcription and speech synthesis models for Mooré language. Then, these models have been used to build a cascaded voice translation system between French and Mooré, since we already got a French-Mooré machine translation model. We collected Mooré audio-text pairs, reaching a total audio duration of 150 hours. Then, We fine-tuned Orpheus-3B and XTTS-v2 for speech synthesis and Wav2Vec-Bert-2.0 for transcription task. After fine-tuning and evaluation by 36 Mooré native speakers, XTTS-v2 achieved a MOS of 4.36 out of 5 compared to 3.47 out of 5 for Orpheus-3B. The UTMOS evaluation resulted in 3.47 out of 5 for XTTS-v2 and 2.80 out of 5 for Orpheus-3B. The A/B tests revealed that the evaluators preferred XTTS-v2 Mooré audios in 77.8% of cases compared to 22.2% for Orpheus-3B. After fine-tuning on Mooré, Wav2Vec-Bert-2.0 achieved a WER of 4.24% and a CER of 1.11%. Using these models, we successfully implemented a French-Mooré Speech-to-Speech Translation system.

Mots-clés

Translation (biology), Languages of Africa, Natural language, Context (archaeology)