How I Fixed TTS Hallucinations Without Regenerating Everything
The audit had done its job. I knew where the generated audiobook didn’t match the manuscript. Now I had another problem. Most of the audio around those errors was already good. The pacing worked. The voices worked. The performances worked. Regenerating an entire chapter to fix one localized problem meant asking the TTS model to recreate all of that again. And generative audio isn’t deterministic…
The audit revealed errors in the generated audiobook. Regenerating an entire chapter to fix a localized issue was not efficient. Instead, treating generated audio as recorded audio allowed for a punch-in approach. Borrowing from the recording studio, a corrupted region could be identified, a replacement generated, and spliced into the existing audio without altering the rest of the performance.
For successful repair, contextual units must be patched, not isolated errors. If a single word is wrong, regenerating the sentence might suffice. If a sentence is corrupted, surrounding exchanges may be regenerated instead. The model should perform the supplied text verbatim, without adding, omitting, paraphrasing, or continuing beyond the supplied text.
Matching the existing master audio was crucial to ensure the replacement blended seamlessly with the surrounding audio. The repaired Chapter 9 reduced the runtime from roughly 11 minutes to about 9 minutes and 51 seconds, removing the 73 seconds of hallucinated dialogue while preserving the rest of the performance.
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