Conference paper Open Access

Towards Personalised Simplification based on L2 Learners' Native Language

Palmero Aprosio, Alessio; Menini, Stefano; Tonelli, Sara; Ducceschi, Luca; Herzog, Leonardo

Dublin Core Export

<?xml version='1.0' encoding='utf-8'?>
<oai_dc:dc xmlns:dc="" xmlns:oai_dc="" xmlns:xsi="" xsi:schemaLocation="">
  <dc:creator>Palmero Aprosio, Alessio</dc:creator>
  <dc:creator>Menini, Stefano</dc:creator>
  <dc:creator>Tonelli, Sara</dc:creator>
  <dc:creator>Ducceschi, Luca</dc:creator>
  <dc:creator>Herzog, Leonardo</dc:creator>
  <dc:description>We present an approach to automatic text simplification that addresses the need of L2 learners to take into account their native language during simplification, tuning the process to the similarities between L1 and L2. In particular, we develop a methodology that automatically identifies ‘difficult’ terms (i.e. false friends) for L2 learners and simplifies them. We evaluate not only the quality of the detected false friends but also the impact of this methodology compared with a standard frequency-based approach to simplification.</dc:description>
  <dc:title>Towards Personalised Simplification based on L2 Learners' Native Language</dc:title>
All versions This version
Views 7272
Downloads 6464
Data volume 9.8 MB9.8 MB
Unique views 6363
Unique downloads 6262


Cite as