- 01
Define the tool evaluation job
Treat “ai 对口型” as a search job to investigate, not as proof that a SEELE feature exists. First clarify the requested job, observe current controls on a bounded test, and document workflow fit and evidence gaps. Write the intended audience, source owner, desired change, protected details, reviewer, and delivery condition before selecting any interface or model. That brief keeps the evaluation specific and makes an unsupported assumption visible early. Before approval, preserve the continuity note, and ask the channel editor to record reversal cost before the final sign-off.
- 02
Prepare inputs for talking avatars and voice
For this topic, assemble authorized identity and voice material, approved script, pronunciation notes, performance intent, and disclosure requirements. Record where each source came from, who may use it, and what must remain unchanged. Use a small representative asset for the first pass, keep the original untouched, and define a fallback route so experimentation cannot silently become the production master. Before approval, preserve the input snapshot, and ask the channel editor to record input provenance before the final sign-off.
- Confirm ownership, consent, and allowed reuse For the working record, preserve the failure note, and ask the release approver to record format readiness before the editorial approval.
- Preserve an untouched source and version history For the working record, preserve the authorization record, and ask the model evaluator to record reversal cost before the editorial approval.
- Name the reviewer and acceptance condition For the working record, preserve the rights memo, and ask the claims reviewer to record control availability before the editorial approval.
- 03
Test observable controls for ai 对口型
A bounded evaluation should inspect lip synchronization, pronunciation, timing, expression, identity fidelity, editability, and audio quality. Change one meaningful variable at a time and record the date, workspace, account context, input, setting, result, and failure. Topic selection can prioritize the question, but it does not establish availability, quality, speed, licensing, or a supported SEELE workflow. For the working record, preserve the claim inventory, and ask the creative lead to record claim scope before the production checkpoint.
- 04
Review evidence, safety, and policy boundaries
Never clone or imitate a voice without permission, fabricate a testimonial, or imply that a real person delivered the message. Any identifiable face, body, or voice requires explicit permission, a legitimate purpose, disclosure where required, and a human check against impersonation or deceptive endorsement. For third-party products, competitors, plans, models, and platform rules, attach a verification date and primary source; an absent statement is an evidence gap rather than proof of a limitation. For this decision, preserve the decision history, and ask the delivery owner to record claim scope before the final sign-off.
- 05
Approve a reversible production handoff
Before advancing “ai 对口型”, confirm speaker consent, compare the performance with the script, inspect sync and artifacts, and disclose synthetic media. Document remaining manual work, unresolved evidence, destination requirements, and the person accepting the result. The handoff should preserve sources and test notes, allow correction, and avoid promises about output quality, turnaround, business performance, publishing, or access that the evidence does not support. In the decision log, preserve the decision history, and ask the production lead to record format readiness before the rights check.