live-transcript-summary

Real-time audio transcription automatically converts speech to text in your open note, identifying speakers and extracting action items incrementally every 60 seconds to provide immediate written records.

Yes, real-time transcription identifies different speakers in an interview and can learn their real names, applying predefined templates to differentiate voices for clearer, structured written records.

You can summarize a lecture while recording by using automatic scene detection to apply lecture templates, processing only new audio segments every 60 seconds to save tokens and generate incremental summaries.

Yes, real-time summarization works without external dependencies, directly monitoring audio from the current WPS Note environment to transcribe spoken content and list action items automatically.

The best way to extract action items during a live meeting is to use incremental audio processing that detects the meeting scene, differentiates speakers, and automatically lists actionable tasks within your note.

To complete unfinished content in the live transcript, you can use on-demand completion prompts by typing "***" to trigger the Skill to finalize the current transcribed segment.