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Contextual Density Ratio for Language Model Biasing of Sequence to Sequence ASR Systems
In this work, we propose a contextual density ratio approach for both training a contextual aware E2E model and adapting the language model to named entities.
On the Prediction Network Architecture in RNN-T for ASR
In contrast to some previous works, our results show that Transformer does not always outperform LSTM when used as prediction network along with Conformer encoder.
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