I built Arc-Transcriber, which does ASR-NL in 1-step. Every 100 ms, one model returns the transcript plus: - Names linked to a list you give it (a roster, contacts, product names); new names are flagged "not on the list" - Numbers with their values (scores, clocks, money, dates) - Speakers and roles; - Sound and channel events (telephone audio, clipping, poor audio) - Whether the speech was addressed to an assistant. The usual ASR, then NER, then entity-linking and then LLM chain is collapsed into the model's own heads, so live "fact-checking" against your list happens inside the stream, not in a second pass. Currently it has two variants Arc mini (which uses moonshot pretrained encoder) and second Arc-v1 (which uses parakeet pretrained encoder). Weights: huggingface.co/WhissleAI/arc-v1.1 Code and CLI: github.com/WhissleAI/arc_transcriber   submitted by   /u/Working_Hat5120 [link]   [comments]