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LLMs can guide phoneme editing to create synthetic accented speech from just a handful of examples, substantially improving ASR accuracy where training data is scarce.
Successfully converting accents requires balancing accent modification with speaker identity preservation, a challenge that this survey unpacks by tracing the evolution of techniques from DSP to neural methods.
