Developer Recovers Lost Speaker Labels in Audio Dataset Using Voice Embeddings

A developer working on a voice conversion application encountered a labeling problem where collected audio samples lost their speaker identities, leaving files tagged only as generic identifiers like spk7 through spk18. To recover the correct names, the developer used CAM++ speaker embeddings already integrated into the app, matching unlabeled anchors against a gallery of labeled raw source files via cosine similarity. To improve accuracy, embeddings were extracted from 12 distributed windows per audio file and averaged after discarding silent segments, rather than relying on a single short clip. Matches were categorized into three confidence levels — certain, uncertain, or no match — based on similarity score thresholds, with human review recommended for borderline cases. The approach essentially applied classical speaker verification techniques to rebuild a lost speaker-mapping configuration file from the voice data itself.