An audio prompt can request words, time ranges, speaker labels, and uncertainty, but these are different outputs with different failure modes. During overlapping speech, a transcript may contain words without a defensible speaker assignment. Use neutral speaker IDs until identity is independently established. Mark overlap spans and unintelligible segments rather than forcing one clean dialogue. If a statement would change an operational decision, replay the original audio near that time and compare it with the transcript. A speaker label is a hypothesis, not proof of who was present.
Audio prompts: mark overlapping speech before assigning speakers
Decision in practice
A driver calls the warehouse at 14:27. Two people talk at once while one says 'forty-four' and another says 'forty-seven'. The initial transcript assigns both phrases to the driver and turns the call into a false agreement about delivery quantity. The revised contract emits an overlap interval, two uncertain phrases, and speaker IDs S1 and S2 without names. A reviewer listens to the source segment and confirms that the driver said 47; the other voice remains unidentified. The inventory discrepancy still requires the signed document check. The audio result cannot replace it.
Audio AU-152; interval 02:13-02:19; overlap: true.
S1: 'forty-seven' [reviewed]; identity: driver [verified separately].
S2: 'forty-four' [uncertain]; identity: unknown.
No consensus statement; quantity remains disputed.
Review: replay source audio from 02:11 through 02:21.Performance and operating cost
For a recording of duration T, one transcription pass is roughly proportional to T in media processed; replaying J disputed spans adds the sum of their durations. Word-level timestamps and diarization increase output size and review time. Send only the relevant interval for a second check, but retain enough lead-in to identify turns. The operational cost is not just model latency: human listening and identity verification may dominate. Track word errors, missed overlaps, and wrong-speaker attributions separately, because a readable transcript can still assign a statement to the wrong person.
Common Mistakes
- Do not force one speaker label across overlapping voices.
- Do not turn an uncertain phrase into an agreement between parties.
- Do not equate a model-assigned speaker ID with a verified identity.
Connected lessons
- Prompt engineering applications
- Prompt Engineering
- Audio prompts: preserve speakers, timestamps, and uncertain words
- Clarification gates: ask only when a missing fact changes the outcome
- Evidence IDs: make generated claims auditable against supplied records
- Document prompts: anchor each field to a page and resolve conflicts
- Image prompts: verify claims against named regions and crops
- Video prompts: disclose sampling gaps around short events
- Cross-modal evidence: keep conflicting observations separate
- Project: reconcile a warehouse evidence packet
- Multimodal prompt evidence decisions
Continue with: Caption and transcript prompts: keep timing, speakers, and sound evidence.
Continue with: Spoken confirmations: repeat the risky field, not the whole form.
Continue with: Meeting prompts: define authorized inputs and evidence.
