Paper Reading AI Learner

Continually learning new languages

2022-11-21 18:24:34
Ngoc-Quan Pham, Jan Niehues, Alexander Waibel

Abstract

Multilingual speech recognition with neural networks is often implemented with batch-learning, when all of the languages are available before training. An ability to add new languages after the prior training sessions can be economically beneficial, but the main challenge is catastrophic forgetting. In this work, we combine the qualities of weight factorization, transfer learning and Elastic Weight Consolidation in order to counter catastrophic forgetting and facilitate learning new languages quickly. Such combination allowed us to eliminate catastrophic forgetting while still achieving performance for the new languages comparable with having all languages at once, in experiments of learning from an initial 10 languages to achieve 27 languages

Abstract (translated)

URL

https://arxiv.org/abs/2211.11703

PDF

https://arxiv.org/pdf/2211.11703.pdf


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