Transformer-based language modeling and decoding for conversational speech recognition

Kareem Nassar

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arXiv · 2001.01140

Transformer-based language modeling and decoding for conversational speech recognition

Kareem Nassar

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Abstract

We propose a way to use a transformer-based language model in conversational speech recognition. Specifically, we focus on decoding efficiently in a weighted finite-state transducer framework. We showcase an approach to lattice re-scoring that allows for longer range history captured by a transfomer-based language model and takes advantage of a transformer's ability to avoid computing sequentially.

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Kareem Nassar. 2020-01-04. Transformer-based language modeling and decoding for conversational speech recognition. https://arxiv.org/abs/2001.01140

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