1. Using Corpora in Translation Studies Research
Dorothy Kenny
SALIS/Centre for Translation and Textual Studies, Dublin City University

2. Outline Part One: General introduction to corpora Part Two:
What they’re good for
How to get your hands on one
Part Two:
Corpora in translation studies research

3. To warm you up: What does ‘cause’ (verb) mean?
What does ‘provide’ mean?
How often is the passive voice used in English?
Handouts

4. Tell me something I don’t know…
Not all facts about language are accessible through native-speaker intuition
It’s often impossible to describe meanings of words without reference to the contexts those words occur in
Sometimes you need a lot of data to see patterns
Sometimes you need to count

5. What a corpus can help us see…
cause has negative ‘semantic prosody’
provide has positive ‘semantic prosody’
(see Louw 1993; Stubbs 1995)
in general, passive is used around 10% of the time in English (see Halliday 1991)

6. Corpus
a collection of naturally-occurring texts that are the object of literary or linguistic study
held in electronic form
thus amenable to (semi-)automatic processing
usually assembled in some principled way
often highly structured, containing very carefully selected texts
compiled for a purpose
eg linguistic analysis, lexicography, Natural Language Processing, translation research…
or a by-product of another activity
eg parliamentary debates (and their translations in bilingual or multilingual parliaments)

7. Well-known monolingual corpora
British National Corpus (100m words)
The Bank of English (524m words)
free access to a sample of 56m words at
The entire World Wide Web

8. Corpora and corpus processing software
Provide:
a (relatively) objective basis for commentary on linguistic phenomena, or linguistic realizations of, eg, social phenomena
a resource for quantitative and qualitative research
the ability to access and manipulate (sort, display, annotate) vast quantities of data, thus facilitating analysis by humans

9. Access to corpora web access purchase own copy (eg BNC)
Bank of English, BNC,IDS
free access to ‘sampler’
access to larger corpus by subscription/permission
purchase own copy (eg BNC)
create your own corpus

10. Web access to corpora: corpus processing software
Web-accessible corpora have dedicated interfaces that allow users, eg, to:
choose texts/sub-corpora
search the corpus for instances of a particular word (results in KWIC concordance format)
display and sometimes sort results

11. Sample search:Cobuild Bank of English

12. Sample results: Cobuild Bank of English

13. Web access to corpora: corpus processing software
More sophisticated interfaces, eg, Cosmas I* (IDS in Mannheim), allowed searches for:
all forms of a lemma
gehen gets gehe, ging, gehst, geht, etc.
all compounds formed from a search word
Möbel gets Gartenmöbel, Möbellager, etc.
all forms derived from a search word
Kind gets Kindchen, kindlich, etc.
*replaced in 2003 by Cosmas II

14. Building your own corpus - basic design issues
Written vs spoken vs written and spoken
Static vs dynamic (monitor)
Synchronic (time of production?) vs diachronic
General reference vs specialised
Monolingual vs bilingual vs multilingual
Domains to be covered
Text types to be covered
Level of annotation: raw vs annotation with extra-textual info (headers to indicate text title, author, speakers, etc) vs detailed linguistic annotation

15. Raw corpus/clean text Example:
As he weakened, Moran became afraid of his daughters. This once powerful man was so implanted in their lives that they had never really left Great Meadow, in spite of jobs and marriages and children and houses of their own in Dublin and London. Now they could not let him slip away.
from John McGahern’s Amongst Women

16. Corpus annotation: structural and POS tagging
Extract from the British National Corpus:
<p>
<s n=0001><w CJS>As <w PNP>he <w VVD>weakened<c PUN>, <w NP0>Moran <w VVD>became <w AJ0>afraid <w PRF>of <w DPS>his <w NN2>daughters<c PUN>.
<s n=0002><w DT0>This <w AV0>once <w AJ0>powerful <w NN1>man <w VBD>was <w AV0>so <w VVD-VVN>implanted <w PRP>in <w DPS>their <w NN2>lives <w CJT>that <w PNP>they <w VHD>had <w AV0>never <w AV0>really <w VVN>left <w AJ0>Great <w NN1-NP0>Meadow<c PUN>, <w PRP>in spite of <w NN2>jobs <w CJC>and <w NN2>marriages <w CJC>and <w NN2>children <w CJC>and <w NN2>houses <w PRF>of <w DPS>their <w DT0>own <w PRP>in <w NP0>Dublin <w CJC>and <w NP0>London<c PUN>.
<s n=0003><w AV0>Now <w PNP>they <w VM0>could <w XX0>not <w VVI>let <w PNP>him <w VVB>slip <w AV0>away<c PUN>.
</p>
from John McGahern’s Amongst Women

17. Building your own corpus - Getting the Texts
Full texts vs text samples
Sampling
random Sampling or handpicking?
Copyright Permission
Representativeness
difficult concept to apply to textual data
onus is on researcher to document corpus contents very carefully

18. Conversion to electronic form?
Text not available in electronic form:
Scanning + OCR vs Keyboarding
Text available in electronic form
Web pages (see Kilgarriff et al 2006)
Downloads from websites
Full-text databases
Donations from authors/translators
Format texts should be saved in?
.txt? .html? .xml? (know what your software can handle!)
Is alignment necessary?

19. Doing Research Using Corpora
Corpora can help us answer questions, but they also generate questions
In general, passive is used around 10% of the time in English; but nearly 20% of the uses of cause as a verb in my scientific corpus are in the passive voice
Does this tell me something about
the verb cause?
scientific English?
my sample of scientific English?

20. Hypothesis generation and testing
Hypothesis – a tentative claim
eg cause tends to be used more in the passive than other English verbs
hypotheses sometimes emerge from corpus data
corpus-driven research
hypotheses sometimes formed before we look at corpus data
corpus-based research
newly generated hypotheses can be tested against other (often bigger) corpora
cycles of hypothesis formation, testing, refinement, testing… common in corpus research

21. Some early descriptive hypotheses in translation studies
Translations tend to be simpler/more explicit/more conventional than:
other texts in the same language
their source texts
But how do you operationalize notions like simplification, explicitation, normalization in corpus-based research?
Eg, what concrete features of a text show it to be ‘simpler’ than another text?
(See especially, Baker 1993, 1995, 1996)

22. Early phase: Developing methodologies and resources
Eg Question: Are translations really ‘simplified’?
Eg Answer: Compared to what?
source texts?
=> parallel corpus methodology
other texts in the target language?
=> comparable corpus methodology

23. Parallel Corpus
set of source texts in language A alongside their translations into language B (and perhaps languages C, D, E …)
can be bilingual or multilingual
eg English-Norwegian Parallel Corpus (ENPC)
eg European Parliament Proceedings Parallel Corpus
can be unidirectional or bidirectional
eg German-English Parallel Corpus of Literary Texts de->en
eg ENPC en->no and no->en

24. Comparable Corpus Monolingual Comparable Corpus
set of texts translated into a language A alongside texts originally written in that same language
Translational English Corpus (TEC)
+ comparable subset of the BNC
Finnish Comparable Corpus (Mauranen 2004)

25. Early Corpus-based TS: Quantitative Bias?
Attempt to approach translation objectively
Reliance on properties of text that can be measured
Average word length
Average sentence length
Lexical density
Type-token ratio, etc
Focus on monolingual comparable corpora
Focus on general tendencies (or ‘universals’) in translation (Laviosa 2002; Mauranen and Kujamäki 2004)

26. Lexical Density
the ratio of content words to the total number of words in a text
I made the chemicals hotter so they changed.
(4/8 = 50%)
Raising the temperature produced a chemical change.
(5/7 = 71%) (from Gibbons 2003:20)
the lower the lexical density, the ‘simpler’ the text.

27. Type-Token Ratio the ratio of types to tokens in a corpus
eg the TTR for The cat sat on the mat near the log fire is 8/10 (or 80%)
assumed to measure the (lexical) variety in a text:
the higher the TTR, the more varied the text’s vocabulary

28. TTR: An Example
In this piece I rail against the tendency of linguists to write about the philosophy of science as applied to their subject field instead of writing about what languages are like, which is what linguists are supposed to be good at. Unsympathetic critics will no doubt charge that by doing so I instantiate the very kind of behavior that I am railing against.
From Pullum 1991:123
TTR = 49/63 = 78%

29. TTR continued
In this piece I rail against the tendency of linguists to write about the philosophy of science as applied to their subject field instead of writing about what languages are like, which is what linguists are supposed to be good at. Unsympathetic critics will no doubt charge that by doing so I instantiate the very kind of behavior that I am railing against. This is not so. I am complaining about unproductive metalevel discussion, which consists of linguists talking about doing linguistics instead of doing it. By offering a critique of such work, I am operating at a meta-metalevel, talking about linguists talking about doing linguistics instead of doing it. There is a difference.
TTR = 66/115 = 57%

30. Type/Token Ratio is extremely sensitive to text length
the longer the text is, the lower the TTR is (normally)
solution: calculate the TTR for successive chunks of texts (eg every 100 or 1,000 words), and then take an average count at the end (standardized TTR)
but even standardized TTRs are problematic as a marker of simplicity/complexity as they can’t capture the difference between hard words and easy words
eg fire vs conflagration

31. Operationalizing ‘Simplification’
If translated texts are somehow ‘simpler’ than original texts in the same language, then they might have:
shorter average word length
shorter average sentence length
lower lexical density
lower standardized type-token ratios
compared to originals…

33. Initial Results: Investigating Simplification (Laviosa 1998a)
Corpus: newspaper articles translated into English, and newspaper articles originally written in English
Tool: WordList in WordSmith Tools
Results
lexical density: lower in translated articles
average sentence length: lower in translated articles
standardized type/token ratio: no significant difference

34. Initial Results: Investigating Simplification (Laviosa 1998b)
Corpus: fiction translated into English, and fiction originally written in English
Tool: WordSmith Tools WordList
Results
lexical density: lower in translated articles
average sentence length: higher in translated articles
standardized type/token ratio: no significant difference
but translations make greater use of high frequency words than do non-translations = core patterns of lexical use

35. Combining Quantitative and Qualitative Research
Investigating Explicitation (Olohan and Baker 2000)
Hypothesis: Translators’ (unconscious?) tendency to be more explicit than other writers in the same language will be visible in their greater use of optional explicitating grammatical elements
Eg: that after ‘He says that Mozart was a wonderful composer’
Compare: ‘He says Mozart was a wonderful composer’
Corpus: TEC and BNC

36. Optional that as seen in concordance lines
Jeux à deux is the circle, which is to say that the duration of the game has ne
nocuous actions in reality, which is to say that the distance must also be maint
sped you hideously. Rock of branches, say that it roars. The fields, as the f
ue ink, Yevgenia Wdowin, but it doesn't say that the eggs in the basement are go
sk what smells so awful, and it doesn't say that my mother hasn't uttered a word
ad in mind for you, then the people who say that Russians stink are right." Dear
upstairs to wait for a moment. He is to say that the stairs are blocked because
n his cigar. It occurred to Vogtmann to say that an apt mode of expression avoid
company with her share. Today she could say that she had made the right decision
must change its owner. I believe I can say that Herr Urban's thoughts are also
n to express our concern. I think I may say that he shares our view.' 'I've got
cking off immediately, I just wanted to say that you would get all the support y
e was not there, but had left a note to say that she had driven to the hospital
happened to Franz prompts me to lie. I say that he has gone off to work in his
orm of institution. What I am trying to say, though, is that this institution is
tecting suspicion, although he couldn't say that he made a deliberate habit of

37. Investigating Explicitation (Olohan and Baker 2000; Olohan 2003, 2004)
Optional that in reporting structures built around SAY and TELL
that far more common in translated English than in original English
factors conditioning inclusion of that:
formality; matrix verb; potential ambiguity;
long adverbials; cognitive complexity
attempt not just to describe, but also to explain the specificities of translation

38. But what about the Source Texts? (Kenny 2005)
Can patterns of inclusion/exclusion of optional that be influenced by patterns for dass in German source texts?
Oberflächlich zufriedengestellt sagte er, dass er sowieso Zeitungen kaufen und telefonieren wolle.
Superficially satisfied, he said that he wanted to buy newspapers and make a telephone call anyway.
Corpus – German-English Parallel Corpus of Literary Texts (GEPCOLT)
Looked at SAY + zero connective vs SAY+ that

39. SAY + that vs zero-connective: Results (Kenny 2005)
optional that used with SAY in 157 cases
78 optional uses of that with SAY coincide with a dass in the ST
79 coincide with a zero-connective in the ST
If you see that, there’s a 50/50 chance that dass was in the ST
zero-connective used with SAY in 219 cases
46 coincide with a dass in the ST
173 coincide with a zero-connective in the ST
If you don’t see that, then eight out of ten times there was no dass in the ST either

40. SAY + that vs zero-connective: Results (Kenny 2005)
patterns of omission of that follow patterns of omission of dass; but patterns of inclusion of that cannot be explained by the ST
dass to 0 shifts do happen (46), but they’re not as common as 0 to that shifts (79)
overall tendency is towards grammatical explicitation

41. From the General to the Particular
Much CTS focuses on general patterns in translated text (see Mauranen and Kujamäki 2004)
Search for generalizations inevitably leads to the recognition of particularities, eg the distinctive behaviour of individual translators
Translators’ individual styles come into focus
Baker (2000), Kenny (2001), Saldanha (2004, 2005)
Winters (2004, 2005), Olohan (2004:Chapter 8), Bosseaux (2007)

42. General Features of Translation vs Features of Translator Style
Eg Kenny (2001)
focuses on lexical creativity/normalisation
uses German-English Parallel Corpus of Literary Texts
uses frequency-ranked word list (WordSmith) to find
creative once-off words in the STs, and
words or clusters of words peculiar to one writer
Uses concordancer (WordSmith) to find creative collocations (node=Auge ‘eye’)
Uses parallel concordancers (Multiconcord) to find translations in the TTs

43. Clusters: Sample Results for John Brownjohn (from Natascha Wodin’s (1983) Die Gläserne Stadt)
Und plötzlich im Parterre das Schrillen des Telefons. Helmut. Um diese Zeit konnte nur er es sein.
Suddenly the phone rang—Helmut--it couldn't be anyone else at this hour.
Das Schrillen des Telefons. Nur zwanzig Minuten diesmal. Ihre Anmeldung Moskau. L's russisches Allo ... die rauhe Oberfläche einer Birne.
The phone rang. Only a twenty-minute delay this time. Your call to Moscow, L's Russian "Allo?"--husky as only his voice could be.
Das Schrillen des Telefons unter der Bettdecke.,
The telephone rang beneath the bedclothes..
Das Schrillen des Telefons unter der Bettdecke.
Again the telephone rang beneath the bedclothes.

44. Writer-specific forms: Sample Results for Malcolm Green (from Gerhard Roth (1986) Am Abgrund)
Da kommt der Staatsbeamte herein und verlangt den Herrn Irrenwäscher zu sprechen.
Then the government official enters and asks to speak to the head madmen-washer.
Der Herr Irrenwäscher kommt auf einem Fahrrad angeradelt und hat eine Fetten.
The head madmen-washer arrives by bicycle, he's as pissed as a fart.
»Das weiß ich selber«, gibt der Herr Irrenwäscher frech zurück
"You're telling me!" the madmen-washer replies impudently.
Der Herr Irrenwäscher ist ein fülliger, behäbiger Mann.
The head madmen-washer is a portly, comfort-loving man.

45. Homing in on the translator’s voice
Whose voice do we hear in translation? Whose point of view do we share? The author’s? The translator’s? Both?
Can we develop methodologies that allow us to show systematic differences between translators, and thus the specific voice of each individual translator? (handout)
Bosseaux (2007),Saldanha (2005), Winters (2004, 2005)
integrate narratological structure, deixis, modality, typography, etc into data- and theory-rich studies of the translator’s presence in translation.
B. and W. look at different translations of the same source text(s)
S. looks at several translations by two translators of different source texts, but from the same source langauge(s)

46. Winters 2005 Bilingual parallel corpus One ST Two TTs
F Scott Fitzgerald’s (1922)The Beautiful and Damned
Two TTs
both into German
both published in 1998
TT1 by Hans-Christian Oeser
TT2 by Renate Orth-Guttmann
Focuses on aspect of the TL that does not have a counterpart in the SL – German modal particles
Research initially data-driven

47. Winters 2005
FSF: He considered, nevertheless, that he had given her an object-lesson and that the matter was closed…
ROG: Immerhin, sagte er sich, habe er ihr eine Lektion erteilt und damit sei der Fall wohl erledigt.
HCO: Nichtsdestoweniger war er der Meinung, daß er ihr einen Denkzettel verpaßt hatte und daß die Sache damit erledigt war…

48. Bennett (1994) distinguishes:
Interplay between corpora and theoretical translation studies: Translation Units (Kenny 2004 & forthcoming)
Bennett (1994) distinguishes:
translation atoms
translation focus
text as macro-unit
For technologists working in Natural Language Processing translation units are segments of ST aligned with segments of their TT

49. Translation Units DTS approach (Toury 1995)
Coupled pairs of ST and TT segments whose boundaries are identified by the analyst, according to ‘no-leftovers principle’
‘Thus, the analyst will go about establishing a segment of the target text, for which it would be possible to claim that – beyond its boundaries – there are no leftovers of the solution to a translation problem which is represented by one of the source text’s segments, whether similar or different in rank and scope.’ (Toury 1995:78-79).

50. Translation Units in NLP (Kraif 2003)
Lexical correspondences
Stable semantic equivalents
Pairing in a corpus a regular occurrence
Useful for bilingual lexicon extraction
Translation Equivalents
Context-bound, possibly once-off pairings
Considered as ‘noise’ in bilingual lexicon extraction

51. Looking for Translation Units in a Parallel Corpus
Interested in :
extended units of meaning and translation units
context ‘independence’ and context dependence
text as macro-translation unit
harnessing potential of corpora to uncover groups of related instances
Assume:
TUs are mutually defining ST-TT segments
search will begin in one language but shuttle back and forth between the SL and the TL
variable TUs (though not normally exceeding clause)

52. Concordance of mit aller Kraft in Gepcolt
ff angefroren sein mußte. Sie versuchte mit aller Kraft, bei klarem Verstand zu
n aus den Gedanken, in denen er steckt, mit aller Kraft herausziehen, doch selbs
e Stopfnadel aus meinem Handarbeitszeug mit aller Kraft, und wenn ich sage Kraft
ahrtendolch in Pension ist, und posiert mit aller Kraft wie auf Sophies Bruderfo
hließend ersticht er die tote Schwester mit aller Kraft. Dann ist er endlich dam
der Kurt Lukas war, schien sein Messer mit aller Kraft in die Hündin zu treiben
hle Bäume vor dem Feld, der Mann rannte mit aller Kraft, das sah ich an den gewö
tarre der Meereisdecke ziehen die Hunde mit aller Kraft nach der nächstgelegenen
ultern gegen die Matratze, stemmte mich mit aller Kraft gegen seinen Amoklauf, e
hte lebenden Embryo-Gesichter, scheinen mit aller Kraft von der Sonne angezogen
eren Glas-Röhrchen auf ihr Blut warten, mit aller Kraft und Empörung auf den Fuß

53. Mit aller Kraft examples (Tables 1 and 2)
What can we say about the:
boundaries of TUs?
No left-overs? Attentional focus on ST? Macro-unit?
stability of translation equivalents/lexical correspondences?
context (or co-text) dependence

54. Context Dependence
Eri wehrte sich zwar mit aller Macht dagegen, verurteilt zu werden
hei resisted being convicted with all hisi might
Siej stößt mit dem Stuhl mit aller Gewalt gegen die Türe.
Shej beats the chair against the door with all herj might
man hieb auf ihn von der Seite ein, mit aller Wucht
he was being lashed by someone at his side with the utmost weight and force

55. Text as Macro-Unit (from Wodin 1983/1986)
Sein gebräuntes Gesicht lacht in den Falten. Das Lachen eines Apfeldiebes. (Par. 125)
His tanned face was creased with laughter, the laughter of a boy stealing apples.
L mit seinem neuen, schlanken, verjüngten Körper, mit seinem alten Apfeldieblachen im Gesicht. (Par. 582)
I couldn’t take my eyes off L, with his new, slim, rejuvenated body and his old, inimitable, mischievious smile.

56. Translation Units - Conclusions
ST segment subject to attentional focus, translation atoms and translation macro-unit can all differ, even on a single occasion
Context dependence can’t be assumed to indicate a once-off idiosyncratic translation; sometimes it’s the norm

57. Conclusions
Corpora
provide a more objective basis for studies of translation, statements about translator behaviour
allow us to zoom in and out, from general to particular and back again
allow synthesis of different approaches (cognitive, empirical, etc)
help us to refine key notions in translation theory

58. The Future?
Better contextualization of studies/results, integrating other sources of data
More sophisticated methodologies and analyses
More varied corpus types
Eg multimodal corpora – audiovisual corpora, sign language corpora, etc
Mainstreaming of basic corpus processing

59. References .
Baker, Mona (1993) ‘Corpus Linguistics and Translation Studies. Implications and Applications’, in Mona Baker, Gill Francis and Elena Tognini-Bonelli (eds), Text and Technology: In Honour of John Sinclair Amsterdam and Philadelphia: John Benjamins
Baker, Mona (1995) ‘Corpora in Translation Studies: An Overview and Some Suggestions for Future Research’, Target 7(2):
Baker, Mona (1996) ‘Corpus-based Translation Studies: The Challenges that Lie Ahead’, in Harold Somers (ed) Terminology, LSP and Translation: Studies in Language Engineering, in Honour of Juan C. Sager Amsterdam and Philadelphia: John Benjamins,
Baker, Mona (2000) Towards a Methodology for Investigating the Style of a Literary Translator’ in Target 12(2):
Bennett, Paul (1994) ‘The Translation Unit in Human and Machine’ Babel 40:1,
Bosseaux, Charlotte (2007) How Does it Feel? Point of View in Translation Amsterdam/New York: Rodopi.
Gibbons, John (2003) Forensic Linguistics. An Introduction to Language in the Justice System Oxford: Blackwell Publishing.
Haller, Helmut, Roeland Van Hout and Jeanine Treffers-Daller ‘Lexical Richness in the Spontaneous Speech of Bilinguals’ in Applied Linguistics 24(2):
Kenny, Dorothy (2001) Lexis and Creativity in Translation: A Corpus-based Study Manchester: St. Jerome.
Kenny, Dorothy (2004) ‘Die Übersetzung von usuellen und nicht unusuellen Wortverbindungen vom Deutschen ins Englische’ in Kathrin Steyer (ed) Wortverbindungen – mehr oder weniger fest. Institut für Deutsche Sprache Jahrbuch 2003 Berlin/New York: Walter de Gruyter,
Kenny, Dorothy (2005) ‘Parallel Corpora and Translation Studies: old questions, new perspectives? Reporting that in Gepcolt. A case study’ in Geoff Barnbrook, Pernilla Danielson and Michaela Mahlberg (eds) Meaningful texts: the extraction of semantic information from monolingual and multilingual corpora London/New York: Continuum,
Kenny, Dorothy (forthcoming) ‘Translation Units and Corpora’ in Alet Kruger and Kim Wallmach (eds) Corpus-based Translation Studies: More Research and Applications Manchester: St. Jerome
Kilgarriff, Adam, Michael Rundell and Elaine Uí Dhonnchadha (2006) ‘Efficient corpus development for lexicography: building the New Corpus for Ireland’, Language Resources and Evaluation 40(2):
Kilgarriff, Adam and Gregory Grefenstette (2003) ‘Web as Corpus’, Computational Linguistics 29(3):
Kraif, Olivier (2003) ‘From translational data to contrastive knowledge’ International Journal of Corpus Linguistics 8:1, 1-29.

60. References continued
Laviosa, Sara (1998a) ‘The English Comparable Corpus: A Resource and a Methodology’ in Lynne Bowker, Michael Cronin, Dorothy Kenny and Jennifer Pearson (eds), Unity in Diversity? Current Trends in Translation Studies Manchester: St. Jerome,
Laviosa, Sara (1998b) ‘Core patterns of lexical use in a comparable corpus of English narrative prose’ Meta 43(4):
Laviosa, Sara (2002) Corpus-based Translation Studies. Theories, Findings, Applications Amsterdam/New York: Rodopi.
Mauranen, Anna (2004) ‘Corpora, universals and interference’, in Anna Mauranen and Pekka Kujamäki (eds) Translation Universals. Do they exist?, Amsterdam and Philadelphia: John Benjamins,
Mauranen, Anna and Pekka Kujamäki (2004) (eds) Translation Universals. Do they exist? Amsterdam and Philadelphia: John Benjamins.
Olohan, Maeve (2003) ‘How frequent are the contractions? A study of contracted forms in the Translational English Corpus’ Target 15:59-89.
Olohan, Maeve (2004) Introducing Corpora in Translation Studies London and New York: Routledge.
Olohan, Maeve and Mona Baker (2000) ‘Reporting that in Translated English: Evidence for Subconscious Processes of Explicitation?’ Across Languages and Cultures 1:
Saldanha, Gabriela (2004) 'Accounting for the Exception to the Norm: a Study of Split Infinitives in Translated English', Language Matters 35(1):39-53.
Saldanha, Gabriela (2005) The Translator's Style: A Corpus-based Exploration Unpublished PhD thesis. Dublin: Dublin City University.
Toury, Gideon (1995) Descriptive Translation Studies and Beyond Amsterdam and Philadelphia: John Benjamins.
Winters, Marion (2004) ‘German Translations of F. Scott Fitzgerald’s The Beautiful and Damned – A Corpus-based Study of Modal Particles as Features of Translators’ Style’. In: Ian Kemble (ed.) Using Corpora and Databases in Translation Portsmouth: University of Portsmouth,
Winters, Marion (2005) A corpus-based study of translator style: Oeser’s and Orth-Guttmann’s German translations of F. Scott Fitzgerald’s The Beautiful and Damned Unpublished PhD thesis. Dublin: Dublin City University.