Three-Character Quality Gate Loophole Taught a Speech Model a Faulty Habit

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A developer training a text-to-speech model discovered that a flaw in the corpus quality-filtering logic caused the model to consistently append meaningless sounds at the end of sentences. The corpus pipeline used Whisper to transcribe TTS-generated audio and discarded clips where transcriptions contained more than three inserted characters not found in the original script. Short hallucinations of one or two characters routinely passed this threshold and were included in training data across roughly 200 clips per voice. The model, trained on 12 voices, learned to reproduce this pattern of appending brief extra sounds. The problem went undetected initially because Whisper itself fails to transcribe very short audio artifacts, and only waveform-envelope analysis revealed the defect.

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