Transcribing a Lecture and Transcribing a Caller Are Not the Same Problem
说明与用途
长时段讲座转录与实时电话通话需要不同策略:优化录音、按停顿分块、保留时间戳、结构化输出以及领域特定术语验证。
问题
Speech‑to‑text for long‑form lectures and real‑time phone calls face fundamentally different constraints, leading to distinct failure modes and evaluation priorities.
结果
By treating lecture and call transcription as separate problems, focusing on capture conditions, chunking strategy, structured extraction, and domain‑specific evaluation, the team achieved higher perceived quality and reliability without relying on model upgrades.
工作流
- 1. Capture audio with correct sample rate and format, handling app backgrounding and screen lock.
- 2. For lectures, chunk audio around natural pauses with overlap, keep timestamps, and structure summaries with headings and definitions.
- 3. For calls, design turn‑based confirmation of identifiers, validate downstream, and build a repair ladder with exit options.
- 4. Store raw transcript, audio, and timestamps for all cases.
- 5. Evaluate using domain‑specific term accuracy rather than aggregate WER.
- 6. Tune latency settings per turn for calls, balancing endpointing aggressiveness.
- 7. Use larger models or second passes only for batch lectures where latency is not critical.
- 8. Monitor structured extraction fields for call failures, not entire calls.
证据
The single biggest accuracy win on the note‑taking side had nothing to do with the transcription model. It was recording conditions.
Word error rate treats every word as equal. Users do not.
On a phone line, you are transcribing through a straw
- 记录日期: 2026-09-18T05:30:35.100Z