Research on the Building of Emotion Metaphor Corpus Based On Machine Translation
Xiaona Jiang
Journal of Digital Information Management, Vol. 15, No. 4, 2017.
DOI: 
Link: http://dline.info/fpaper/jdim/v15i4/jdimv15i4_5.pdf
Abstract:
Metaphor is a result of emotion
conceptualization hidden in human language. Due to the
complexity and abstraction of human emotion, it is difficult
to calculate and create a model for it. However, emotion
modeling and calculation is of great significance in the
process of machine translation (MT). Usually, incorporating
the calculation of emotion metaphors in machine
translation could make the language much more vivid and
meet the standards of faithfulness, expressiveness and
elegance in translation. Normally, calculation of emotion
metaphor adopts machine learning and pattern
identification, and it requires the samples from emotion
metaphor corpus of large scale and high quality. The thesis
builds an English and Chinese bilingual corpus with
affluent emotion metaphors and supports data to emotion
metaphor calculation by machine translation. In the
process of building emotion metaphor corpus, 5 main
procedures including theoretical framework, design
principles, data collection, data annotation and index
monitoring are illustrated. Finally, machine translation
experiment has been done in emotion metaphor corpus
built in this thesis, which adopts same recurrent neural
network and LSTM mnemon to compare with existing
machine translation corpora. Result shows that the
emotion metaphor corpus built in this thesis is able to
express emotion metaphor in machine translation.