Prompt-to-Correct: Automated Test-Time Pronunciation Correction with Voice Prompts
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
Authors
- Vineet Gandhi (ORCID: https://orcid.org/0000-0001-8861-7731)
- Neil Shah (ORCID: https://orcid.org/0000-0003-3261-8430)
- A S Kashyap
Institutions
- Indian Institute of Technology Hyderabad (IN)
Publication Details
- Published
- 2025-03-12
- DOI
- https://doi.org/10.1109/icassp49660.2025.10889824
- Primary Topic
- Speech Recognition and Synthesis
- Type
- article
- Field-Weighted Citation Impact
- 0.00