Joachim Bingel

3 paper cards in Mova's library · 2017–2018

Joachim Bingel wrote 3 of the papers Mova reads, in 2017–2018, most of them on Machine translation; often with Anders Søgaard, Marcel Bollmann, Carolina Scarton.

The profile is the library's match of the name; two people with one name are not always told apart.

Papers

Multi-task learning for historical text normalization: Size matters (2018)
The paper asks when multi-task learning helps historical normalisation. It tests an encoder-decoder model with and without auxiliary tasks on 10 datasets from 8 languages, from German and English to Hungarian, Icelandic, Slovene, Spanish, Portuguese and Swedish. Most datasets either always gain or always lose from…
Learning attention for historical text normalization by learning to pronounce (2017)
The paper treats historical normalisation as a character-level transduction with an encoder-decoder RNN, so no explicit character alignment is needed.
Learning How to Simplify From Explicit Labeling of Complex-Simplified Text Pairs (2017)
End-to-end simplification models learn from parallel sentence pairs and cannot say what they learned. The authors instead find the simplification operations (deletion, replacement, addition, reordering and others) automatically in a parallel corpus, by aligning complex and simple words, and label each source token…