Understanding Speaker Drift in TTS Batches

Speaker drift is the most common anomaly in TTS batches. It happens when the TTS model's output gradually changes characteristics - pitch, timbre, speaking rate - across a batch of files.

File 1 sounds crisp and consistent. File 50 is slightly different. File 200 is noticeably different from file 1. But because the change is gradual, each file sounds fine compared to its immediate neighbors.

This is why spot-checking fails for drift detection. If you listen to file 1, then file 10, then file 20, everything sounds fine. The drift only becomes apparent when you compare files that are far apart in the batch.

Drift happens for several reasons. Long generation sessions cause model state to shift. Temperature and sampling parameters create cumulative variation. GPU memory states fluctuate during extended runs.

Automated detection works by extracting speaker embeddings from each file and tracking consistency across the batch. A consistent batch clusters tightly in embedding space. A drifting batch shows a clear trajectory - the embeddings gradually migrate.

When TTSAudit detects drift, it tells you exactly which files are affected so you can regenerate only those, rather than re-running the entire batch.