A Parallel Corpus-driven Approach to Bilingual Oenology Term Banks: How Culture Differences Influence Wine Tasting Terms

A Parallel Corpus-Driven Approach to Bilingual Oenology Term Banks: How Culture Differences Influence Wine Tasting Terms Vincent Xian Wang Xi Chen Department of English University of Macau vxwang@um.edu.mo Department of Chinese and Bilingual Studies The Hong Kong Polytechnic University Department of English, University of Macau yb77703@um.edu.mo Songnan Quan Chu-Ren Huang Department of Chinese and Bilingual Studies The Hong Kong Polytechnic University songnan.quan@connect.polyu.hk Department of Chinese and Bilingual Studies The Hong Kong Polytechnic University The HK PolyU-PKU Research Centre on Chinese Linguistics churen.huang@polyu.edu.hk Abstract This paper describes the construction of an English-Chinese Parallel Corpus of wine reviews and elaborates on one of its applications – i.e. an E-C bilingual oenology term bank of wine tasting terms. The corpus is sourced from Decanter China, containing 1211 aligned wine reviews in both English and Chinese with 149,463 Chinese characters and 66,909 English words. It serves as a dataset for investigating cross- lingual and cross-cultural differences in describing the sensory properties of wines. Our log-likelihood tests revealed good candidates for the Chinese translations of the English words in wine reviews. One of the most challenging features of this domain-specific bilingual term bank is the dominant many-to-many nature of term mapping. We focused on the one-to-many English-Chinese mapping relations of two major types: (a) the words without a single precise translation (e.g. “palate”) and (b) the words that are underspecified and involve ‘place-holder’ translation (e.g. “aroma”). Our study differs from previous bilingual CompuTerm studies by focusing on an area where cultural and sensory experiences favour many-to-many mappings instead of the default one-to-one mapping preferred in scientific and jurisprudential areas. This necessity for many-to-many mappings in turn challenges the basic design feature of many state-of-the-art automatic bilingual term-extraction approaches. 1 Introduction The textual data of wines in the field of wine informatics are increasingly accessible to the public through the Internet in this big data era. Wine reviews have been much criticised in terms of the use of metaphors for describing wine- tasting experience that often goes so free that it becomes “difficult to understand” (Demaeker, 2017, p.117). However, Croijmans, Hendrickx, Lefever, Majid and Van Den Bosch (2020) refuted this line of criticism by exhibiting high consistency in the use of wine terms in 76,410 wine reviews they gathered, which also effectively trained a classifier that automatically and rather accurately predicted the wine colour (red, white, or rose) and grape variety (n=30) in the wine reviews that were new to the classifier. Largely consistent with the results of Croijmans et al. (2020), López-Arroyo and Roberts (2014) found wine reviews used a limited repertoire of commonly-used words to convey specialised senses about wine tasting experience, while extending metaphorical applications of the words. The sensory experience of wine tasting was also studied in the frame of “motions” by Caballero (2017), who drew on cognitive linguistic research on motion events to examine the description of the aromas and flavours of wine “travelling” to sensory organs. Caballero gathered 12,000 wine notes in both English and Spanish and identified similarities and …

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