Prompt-to-Correct: Automated Test-Time Pronunciation Correction with Voice Prompts

Abstract

Pronunciation correction is crucial for Text-to-Speech (TTS) systems in production. Traditional methods, which rely on phoneme sequence manipulation, are often cumbersome and error-prone. To address this, we propose Prompt-to-Correct, an editing-based methodology for pronunciation correction in TTS systems using voice prompts. Our approach enables accurate, granular corrections at test-time without the need for additional training or fine-tuning. Unlike existing speech editing methods, we eliminate the need for external alignment to determine edit boundaries. By simply providing a correctly-pronounced reading of a word in any voice or accent, our system successfully corrects mispronunciations while maintaining continuity. Experimental results demonstrate that our method outperforms traditional baselines and state-of-the-art speech editing techniques. Speech samples are available at: https://prompt-to-correct.github.io/P2C