You feed it audio in small slices, anywhere from 80 milliseconds to two seconds long, and it returns text for each slice as it goes. The unusual promise is that the text is final: what it has printed stays printed. Most live transcribers show a draft and fix it a second later, which is fine for a person reading captions but breaks anything downstream, like a translator or an agent that already acted on the first version. This model only emits a word once it has decided that word is stable, and holds the rest back until the next slice.
The dial you control is slice size. At 160 milliseconds you get near-instant captions with a few more errors; at two seconds you get accuracy close to a batch transcription of the whole file. Youdao's own tests put the 160 ms setting close to the full offline Qwen3-ASR it was built from on English and Chinese sets, and ahead of other open streaming models at a similar delay, with typical latency of 200 to 600 milliseconds. You can hand it a list of names or jargon as a hint, and it covers some thirty languages, with Chinese and English as the strong ones.
Under the hood it is a 2B-parameter fine-tune of Qwen3-ASR trained to recognize the longest stretch of text it can safely commit to. It ships with a vLLM backend for throughput, a plain transformers backend, and a ready-made WebSocket server that streams the incremental text to any client.