The aim of this thesis is to present possible implementations of the two Machine Learning tasks of Speech To Text and Text To Intent paired with Named Entity Recognition, in the context of a possible deployment as core technologies exploited by a Virtual Assistant running on board of the next generation Fighter. Indeed, it is the outcome of a six-month long period of Internship in Leonardo Labs, the R&D department of Leonardo SpA, based in Turin. In what the Speech To Text module is concerned, OpenAI Whisper neural network is exploited as base structure to be fine-tuned on the down-stream task, with a dataset generated by collecting audio recordings through a Graphic User Interface implemented through the Python framework Streamlit.