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Building upon the strength of modern large language models (LLMs), generative error correction (GEC) has emerged as a promising paradigm that can elevate the performance of modern automatic speech recognition (ASR) systems. One representative approac
Externí odkaz:
http://arxiv.org/abs/2407.16370
