Synthetic Language Interpretation Modality, Machine Learning

The Synthetic Language Interpretation Modality, Machine Learning (SLIM-ML) is a military use-restricted algorithm devised by the UNSC Office of Naval Intelligence for the computational interpretation and recognition of virtually all forms of human speech, encompassing most 26th century major languages and their variegated dialects. Built by progressive machine learning artificial intelligence-training approaches, the SLIM-ML algorithm was "trained" on 1030 instances of human speech collected from a staggeringly diverse compendium of recorded pieces of human speech spanning centuries of terran history. Founded on this vast "training set" of human speech fragments, SLIM-ML can confidently understand and digitize the speech of virtually any human being alive, regardless of the tone of the speaker's voice, their base language, any regional dialects, or digital distortion (e.g., voices over secure channels that are scrambled for anonymity purposes). SLIM-ML is presently being trained on a repertoire of Covenant languages and dialects, based on massive miscellaneous commercial, historical, and governmental speech fragments provided by the new Sangheili-led Covenant regime. The foundation of the SLIM-ML protocol is the POLYGLOT machine learning framework devised by the Directorate of Fleet Intelligence. 
One of the most impressive implementations of SLIM-ML is in the new Enhanced Capabilities Control system pioneered by the UNSC Special Operations Command and subsequently generally adopted by the UNSC Joint Forces Command and all its subordinate branches. SLIM-ML is programmed aboard AQ99E "Electric Wombat" unmanned drones that have multichannel radios monitoring UNSC MILNET frequencies. Fire mission requests from Special Forces teams on the grounds on MILNET frequencies, if properly authenticated, are automatically understood by the SLIM-ML program aboard Electric Wombat unmanned drones, and are digitized and interpreted by the fighters — no human input required. Once a fire mission request is understood by SLIM-ML, a crimson diamond representing the target reference point for the airstrike appears in the HUD of the forward observer who submitted the request. If SLIM-ML's interpretation is correct, the ground party need only confirm it through their HUD, and an Electric Wombat circling in the skies will deliver the missile strike as planned.
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Category:Office of Naval Intelligence