Engineers Replace Manual Voice Clip Selection with Automated Three-Stage Filter System

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Developers of a voice conversion app faced inconsistent and unscalable manual selection of 4-to-12-second audio anchors from voice actor recordings. To address this, they built a three-stage automated pipeline that filters audio clips for single-speaker content, natural pronunciation, and recording quality. The system begins with 48 equally spaced candidate windows per file, narrows them using pitch and energy analysis, then applies speaker embedding and SQUIM-based quality scoring. As a result, the minimum PESQ score of the anchor set rose significantly from 1.24 to 2.31, and the team compiled a library of over 70 usable anchors. The approach was originally documented in Japanese on the team's engineering blog.

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