- 01
Define the workflow learning job
Treat “talking photo” as a search job to investigate, not as proof that a SEELE feature exists. First turn the query into a repeatable sequence with explicit inputs, review points, and a reversible handoff. 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 revision, preserve the delivery checklist, and ask the production lead to record identity consent before the fallback decision.
- 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 revision, preserve the handoff draft, and ask the policy reviewer to record input provenance before the acceptance review.
- Confirm ownership, consent, and allowed reuse At handoff, preserve the control log, and ask the creative lead to record revision intent before the rights check.
- Preserve an untouched source and version history At handoff, preserve the input snapshot, and ask the model evaluator to record visible continuity before the rights check.
- Name the reviewer and acceptance condition At handoff, preserve the handoff draft, and ask the release approver to record claim scope before the rights check.
- 03
Test observable controls for talking photo
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. At handoff, preserve the brief version, and ask the policy reviewer to record evidence freshness before the evidence refresh.
- 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 the named reviewer, preserve the evidence table, and ask the model evaluator to record evidence freshness before the scope confirmation.
- 05
Approve a reversible production handoff
Before advancing “talking photo”, 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. For a reversible workflow, preserve the continuity note, and ask the delivery owner to record revision intent before the editorial approval.