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Shallow fusion for RNN Transducer
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Shallow fusion for RNN Transducer
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In real-life scenario, there is often a mismatch between the training corpus and the target corpus space.
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External language models (LM) are commonly used to improve WERs for E2E ASR models.
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Therefore, we often use an external language model (LM) to improve the accuracy of the ASR model
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on the target space. Even if the training and testing domain are similar, using external langugage model
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can still help the ASR model if the training corpus is not that large.
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This tutorial shows you how to perform ``shallow fusion`` with an external LM
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This tutorial shows you how to perform ``shallow fusion`` with an external LM
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to improve the word-error-rate of a RNN Transducer model.
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to improve the word-error-rate of a RNN Transducer model.
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