Speech AI from Mauritania

MauriAI builds voice technologies with a focus on Hassaniya and multilingual speech applications.

Founder and researcher: Mohamed Lamine Bewa · Mauritania

HAKEM

Hear an item. Select it from your list.

HAKEM uses frozen speech models to select among supplied text candidates, subtracting a matched digital-silence score. It requires no additional task-specific weight training or recorded enrolment examples of the candidates.

Try the live HAKEM demo · Read the research preprint · MauriAI website

The demo compares candidate scoring with Whisper Tiny transcription followed by text matching, on the same user-supplied recording and list. It is an implementation preview, not an independent replication of the paper's benchmarks.

Research scope: selection from a supplied catalogue containing the correct item. This is a preprint, not yet peer reviewed. It does not establish general transcription accuracy, spontaneous command understanding, or universal language performance.

Privacy: Hassaniya research recordings and the private study catalogue are not distributed here. The demo uses visitors' own audio, processed on its host with temporary framework files. Please use non-confidential test recordings.