Building on my voice and audio-editing background, this is the approach I would bring to a reviewer role. Each evaluation starts with careful listening and the project’s own guidelines.
Listen for background noise, distortion, distracting breaths, abrupt cuts, and uneven volume. Note the timestamp, describe what is audible, and explain how it affects understanding.
Compare the recording with the supplied transcript for missing, added, or incorrect words. Check unclear names and terms against project references, and distinguish accent variation from pronunciation errors.
Use the supplied rubric, review one criterion at a time, and recheck uncertain segments. Organize findings by timestamp, issue, impact, and suggested next step; flag uncertainty instead of guessing.
Part of my recording and audio-editing toolkit. A workspace for voice projects, arranging takes, and working with audio tracks.
Part of my audio-editing toolkit for working with recordings and inspecting waveforms. Useful for replaying short sections and checking edits and level changes alongside careful listening.
An AI tool I use for organizing notes, clarifying instructions, and improving the wording of feedback. On client projects, I would use it only within the project’s AI and data-sharing rules, with final judgments checked by me.
My theater and voice work involves attention to delivery, pacing, pronunciation, and the clarity of recorded speech. Hear my existing character, commercial, corporate, and narration samples in my voice acting portfolio ↗. These demonstrate my voice work; they are not client QA case studies.