Scalable African LAnguage Multimodal AI Framework, an open-source Speech-to-Speech system built to empower African languages in voice-driven applications, starting with Swahili.
Bridge the African linguistic digital divide by providing high-quality, culturally aligned speech and language intelligence systems. SALAMA enables seamless end-to-end voice interaction by converting speech → text → intelligent response → speech.
Three modular components working together for end-to-end voice interaction.
Robust transcription for African languages using Whisper Small, fine-tuned for Swahili speech patterns and noisy environments.
Context-aware reasoning and response generation using UlizaLlama, instruction-tuned for natural Swahili text generation.
Natural, expressive voice synthesis using Facebook MMS (VITS-based), fine-tuned for Swahili prosody and tone.
Designed for extensibility, performance, and real-world impact.
STT, LLM, and TTS can be swapped, upgraded, or fine-tuned independently.
Models fine-tuned for African speech patterns and dialectal variations.
Framework designed to support additional modalities such as vision.
Optimized for low-latency voice interaction in conversational agents.
Simple configuration for integrating new languages or tasks.
Strong performance across all modules, validated on real-world Swahili data.
SALAMA supports six flexible modes for voice and text interaction.
Voice → LLM → Voice. Full end-to-end voice conversation.
Text → LLM → Text. Standard chat interaction.
Voice input, text response via LLM processing.
Text input, voice response with natural synthesis.
Transcription only, no LLM processing.
Synthesis only, no LLM processing.
All SALAMA models are open-source and available on HuggingFace.
Swahili Whisper ASR, fine-tuned speech recognition with 95.4% accuracy.
openai/whisper-smallSwahili instruction-tuned language model for reasoning, Q&A, and dialogue.
Jacaranda/UlizaLlamaSwahili text-to-speech with natural prosody, MOS 4.05/5.0.
facebook/mms-tts-swhSALAMA is open-source under the MIT License. Clone the repository, install dependencies, and start building voice-powered African language applications.