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Lattice-Free MMI Adaptation Of Self-Supervised Pretrained Acoustic Models

2020-12-28 14:53:28
Apoorv Vyas, Srikanth Madikeri, Hervé Bourlard
arXiv_SD
         
Abstract

In this work, we propose lattice-free MMI (LFMMI) for supervised adaptation of self-supervised pretrained acoustic model. We pretrain a Transformer model on thousand hours of untranscribed Librispeech data followed by supervised adaptation with LFMMI on three different datasets. Our results show that fine-tuning with LFMMI, we consistently obtain relative WER improvements of 10% and 35.3% on the clean and other test sets of Librispeech (100h), 10.8% on Switchboard (300h), and 4.3% on Swahili (38h) and 4.4% on Tagalog (84h) compared to the baseline trained only with supervised data.

Abstract (translated)

URL

https://arxiv.org/abs/2012.14252

PDF

https://arxiv.org/pdf/2012.14252.pdf

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