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JEIT: Joint End-to-End Model and Internal Language Model Training for Speech Recognition

By Zhong Meng and others
We propose JEIT, a joint end-to-end (E2E) model and internal language model (ILM) training method to inject large-scale unpaired text into ILM during E2E training which improves rare-word speech recognition. With JEIT, the E2E model computes an E2E loss on audio-transcript pairs while its ILM estimates a cross-entropy loss on... Show more
February 16, 2023
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JEIT: Joint End-to-End Model and Internal Language Model Training for Speech Recognition
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