Abstract
This paper discusses the debatable hypotheses of “Translation Universals”, i. e. the recurring common features of translated texts in relation to original utterances. We propose that, if translational language does have some distinctive linguistic features in contrast to non-translated writings in the same language, those differences should be statistically significant, consistently distributed and systematically co-occurring across registers and genres. Based on the balanced Corpus of Translational English (COTE) and its non-translated English counterpart, the Freiburg-LOB corpus of British English (FLOB), and by deploying a multi-feature statistical analysis on 96 lexical, syntactic and textual features, we try to pinpoint those distinctive features in translated English texts. We also propose that the stylo-statistical model developed in this study will be effective not only in analysing the translational variation of English but also be capable of clustering those variational features into a “translational” dimension which will facilitate a crosslinguistic comparison of translational languages (e. g. translational Chinese) to test the Translation Universals hypotheses.
Funding statement: Funding: National Social Science Fund of China, (Grant/Award Number: “11CYY010”) Program for New Century Excellent Talents in University, Ministry of Education of China, (Grant/Award Number: “NCET-11-0460”) Economic and Social Research Council, (Grant/Award Number: “ES/K010107/1”)
About the authors
Xianyao Hu currently holds a professorship in the College of International Studies at Southwest University in China. He worked as a research associate in the Department of Linguistics and English Language at Lancaster University in 2014. He got his Ph.D. in Translation Studies from East China Normal University in 2006, and had worked as post-doctoral researcher at Beijing Foreign Studies University and Fulbright visiting scholar at the University of California Los Angeles.
Richard Xiao is Professor of Linguistics at Zhejiang University in China as well as Reader in Corpus Linguistics and Chinese Linguistics (Honorary) in the Department of Linguistics and English Language at Lancaster University in the UK. His main research interests cover corpus linguistics, contrastive and translation studies of English and Chinese, and tense and aspect theory. His recent books in these areas include Aspect in Mandarin Chinese (John Benjamins, 2004), Corpus-Based Language Studies (Routledge, 2006), A Frequency Dictionary of Mandarin Chinese (Routledge, 2009), Using Corpora in Contrastive and Translation Studies (Cambridge Scholars, 2010), Corpus-Based Contrastive Studies of English and Chinese (Routledge, 2010) and Corpus-Based Studies of Translational Chinese in English-Chinese Translation (Springer 2015).
Andrew Hardie is Senior Lecturer in the Department of Linguistics and English Language at Lancaster University in the UK. He is Deputy Director of the ESRC Centre for Corpus Approaches to Social Science. His major specialism is corpus linguistics – specifically, the methodology of corpus linguistics, and how it can be applied to different areas of study in linguistics and beyond. He is also interested in the use of corpus-based methods to study languages other than English, especially the languages of Asia, with an especial focus on issues in descriptive and theoretical grammar.
Acknowledgements
This research was undertaken as part of the UK ESRC-funded project “Comparable and Parallel Corpus Approaches to the Third Code: English and Chinese Perspectives” (ES/K010107/1). We are also obliged to the support of the National Social Science Fund of China for the research project (11CYY010) and the Ministry of Education of China under its Program for New Century Excellent Talents in University (grant reference NCET-11-0460).
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Appendix: Linguistic features analysed
| (A) TENSE AND ASPECT MARKERS | ||
| 1 | VBD | Past tense |
| 2 | PEAS | Perfect aspect |
| 3 | VPRT | Present tense |
| (B) PLACE AND TIME ADVERBIALS | ||
| 4 | PLACE | Place adverbials |
| 5 | TIME | Time adverbials |
| (C) PRONOUNS AND PROVERBS | ||
| 6 | FPP1 | First person pronouns |
| 7 | SPP2 | Second person pronouns |
| 8 | TPP3 | Third person pronouns |
| 9 | PIT | pronoun it |
| 10 | DEMP | Demonstrative pronouns |
| 11 | INPR | Indefinite pronouns |
| 12 | PROD | Pro-verb do |
| (D) QUESTIONS | ||
| 13 | WHQU | WH-questions |
| (E) NORMINAL FORMS | ||
| 14 | NOMZ | Nominalizations |
| 15 | GER | Gerunds |
| 16 | NN | Total other nouns |
| (F)PASSIVES | ||
| 17 | PASS | Agentless passives |
| 18 | BYPA | By-passives |
| (G) STATIVE FORMS | ||
| 19 | BEMA | Be as main verb |
| 20 | EX | Existential there |
| (H) SUBORDINATION | ||
| 21 | THVC | That verb complements |
| 22 | THAC | That adjective complements |
| 23 | WHCL | WH-clauses |
| 24 | TO | Infinitives |
| 25 | PRESP | Present participial clauses |
| 26 | PASTP | Past participial clauses |
| 27 | WZPAST | Past participial WHIZ deletion relatives |
| 28 | WZPRES | Present participial WHIZ deletion relatives |
| 29 | TSUB | That relative clauses on subject position |
| 30 | TOBJ | That relative clauses on object position |
| 31 | WHSUB | WH relative clauses on subject position |
| 32 | WHOBJ | WH relative clauses on object position |
| 33 | PIRE | Pied-piping relative clauses |
| 34 | SERE | Sentence relatives |
| 35 | CAUS | Causative adverbial subordinators |
| 36 | CONC | Concessive adverbial subordinators |
| 37 | COND | Conditional adverbial subordinators |
| 38 | OSUB | Other adverbial subordinators |
| (I) PREPOSITIONAL PHRASES, ADJECTIVES AND ADVERBS | ||
| 39 | PIN | Total prepositional phrases |
| 40 | ATTRJ | Attributive adjectives |
| 41 | PRED | Predictive adjectives |
| 42 | R | Total adverbs |
| (J) LEXICAL SPECIFICITY | ||
| 43 | STTR | Standardized Type/Token Ratio |
| 44 | AWL | Average word length |
| (K) LEXICAL CLASSES | ||
| 45 | CONJ | Conjuncts |
| 46 | DWNT | Downtoners |
| 47 | HDG | Hedges |
| 48 | AMP | Amplifiers |
| 49 | EMPH | Emphatics |
| 50 | DPAR | Discourse particles |
| 51 | DEMO | Demonstratives |
| (L) MODALS | ||
| 52 | POMD | Possibility modals |
| 53 | NEMD | Necessity modals |
| 54 | PRMD | Predictive modals |
| (M) SPECIALIZED VERB CLASSES | ||
| 55 | PUBV | Public verbs |
| 56 | PRIV | Private verbs |
| 57 | SUAV | Suasive verbs |
| 58 | SMP | Seem/appear |
| (N) REDUCED FORMS AND DISPREFERRED STRUCTURES | ||
| 59 | CONT | Contractions |
| 60 | THATD | Subordinator-that deletion |
| 61 | STPR | Stranded prepositions |
| 62 | SPIN | Split infinitives |
| 63 | SPAU | Split auxiliaries |
| (O) COORDINATION | ||
| 64 | PHC | Phrasal coordination |
| 65 | ANDC | Independent clause coordination |
| (P) NEGATION | ||
| 66 | SYNE | Synthetic negation |
| 67 | XX0 | Analytic negation |
| (Q) OVERALL TEXTUAL FEATURES | ||
| 68 | ASL | average sentence length |
| 69 | APL | average paragraph length |
| 70 | ASSL | average sentence section length |
| 71 | STW | Short words (≤letters) |
| 72 | LNW | long words (≥letters) |
| 73 | TOP10 | Highest frequency words |
| 74 | LD | lexical density (proportion of lexical words) |
| 75 | GEX | proportion of function words |
| 76 | PUNC | punctuation |
| (R) OTHER FEATURES | ||
| 77 | N | Noun |
| 78 | V | Verb |
| 79 | J | Adjective |
| 80 | M | Number |
| 81 | P | Pronoun |
| 82 | I | Proposition |
| 83 | APPGE | possessive pronoun |
| 84 | AT | Articles |
| 85 | CC | coordinating conjunction |
| 86 | CS | subordinating conjunction |
| 87 | DT | Determiner |
| 88 | GEM | genitive marker |
| 89 | REFM | reformulation marker |
| 90 | FW | foreign word |
| 91 | MD | Models |
| 92 | RP | Particle |
| 93 | WDT | Wh-determiner |
| 94 | WP | Wh-pronoun |
| 95 | WP$ | possessive Wh-pronoun |
| 96 | WRB | Wh-adverb |
©2019 by De Gruyter Mouton
