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

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Published
2025-03-12
DOI
https://doi.org/10.1109/icassp49660.2025.10889824
Primary Topic
Speech Recognition and Synthesis
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article
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article

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

Vineet Gandhi, Neil Shah, A S Kashyap
Speech Recognition and Synthesis
article

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

Vineet Gandhi, Neil Shah, A S Kashyap
article en

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

Indian Institute of Technology Hyderabad (IN)
Quality Education
Openalex Percentile: Top 98%
Speech Recognition and Synthesis
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Prompt-to-Correct: Automated Test-Time Pronunciation Correction with Voice Prompts — Vineet Gandhi, Neil Shah, et al. · (2025) | TGRS Research Map | TGRS