Research & Innovation
Scientific Infrastructure for African Language Technologies
KivuLingua AI develops advanced ASR and TTS systems using open-source frameworks: Whisper, wav2vec 2.0, MMS (Massively Multilingual Speech), SpeechBrain, and Coqui TTS. We evaluate performance through Word Error Rate (WER), Character Error Rate (CER), Mean Opinion Score (MOS) and comparative benchmarking. Our research prioritizes ethical data collection, community ownership, and integration with international open-science ecosystems including Hugging Face and Mozilla Common Voice.
In Progress
Multilingual Speech Recognition for Low-Resource Bantu Languages using Whisper and wav2vec 2.0
Muhigiri Ashuza, CIRUZA Alain, KivuLingua Research Team
In Progress
Community-Driven Corpus Creation for Bantu Language Speech AI: Methodology and Ethical Frameworks
KivuLingua Project & Local Linguistic Communities
Planned
Benchmarking ASR Performance: Word Error Rate and Character Error Rate Analysis for East Congolese Bantu Languages
KivuLingua Technical Team
Planned
Neural Text-to-Speech Synthesis for Endangered Bantu Languages using SpeechBrain and Coqui TTS
CIRUZA Alain, Technical Development Team