2021
History Utterance Embedding Transformer LM for Speech Recognition
ICASSP 2021accepted
History utterances contain rich contextual information; however, better extracting information from the history utterances and using it to improve the language model (LM) is still challenging. In this paper, we propose the history utterance embedding Transformer LM (HTLM), which includes an embeddin…