Moonshine is a cross-platform AI inference core and toolkit designed for executing quantized neural networks locally on edge hardware. It serves as a high-performance runtime for running large language models and speech processing tasks without cloud connectivity.
The project functions as an edge speech-to-text engine and an on-device text-to-speech synthesizer. It enables the creation of voice interfaces by combining real-time transcription, intent recognition, and the ability to generate audible speech from written text using phonetic lexicons.
The system covers several broad capability areas, including speaker diarization to distinguish individual voices, phonetic text processing using the International Phonetic Alphabet, and conversational flow management. It also includes tools for model weight quantization and multicore compute distribution to optimize performance on local hardware.
