Transformer-based language modeling and decoding for conversational speech recognition

2020/01/04 by Kareem Nassar, Nassar, Kareem
Computer Science · #Speech Recognition and Synthesis #Topic Modeling #Natural Language Processing Techniques

paper · pdf · doi:10.48550/arxiv.2001.01140

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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