Identifying fluency parameters for a machine-learning-based automated interpreting assessment system.

Fluency is an important yet difficult-to-measure criterion in interpreting assessment. This empirical study of English-Chinese consecutive interpreting aims to identify fluency parameters for a machine-learning-based automated assessment system. The main findings include: (a) empirical evidence supp...

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Bibliographic Details

Published in:	Perspectives: Studies in Translatology Vol. 32; no. 2; pp. 278 - 295
Main Authors:	Wang, Xiaoman, Wang, Binhua
Format:	Article
Published:	Taylor & Francis Ltd Apr2024
Subjects:	Median (Mathematics) Machine learning Scoring rubrics Dependent variables Empirical research
Online Access:	View this record in EBSCOhost