An Investigation into the Efficiency of Translation

Dictation

Masaru Yamada, Kansai University, OsakaMichael Carl, Copenhagen Business School and

National Institute of Informatics, Tokyo

Goals of the study

● ENJA15: compare translation dictation (Aug. 2015 – Jan. 2016):

– with other translation modes (from-scratch, post-editing)

– between different experienced users (students, professionals)

● JTD16: investigate translation dictation (Feb. 2016 – March 2016):

– learning effects in 6 successive translation sessions

– different behaviour experienced users

● Compare with translation behaviour in other language pairs:

– 150 hours TP data in the TPR-DB

– EN → DA, DE, ES, HI, JA, ZH

Data Acquisition with Translog-IIData Acquisition with Translog-II

ENJA15: Translation Experiment

● Ambition:Investigate variations of human translation processes across different translator profiles and translation modes: translation, post-editing, dictation

● Method:

➔ Translate six short English source texts (110-160 words) from English into Japanese under controlled conditions

➔ Record translation activities: transcribed speech, keystrokes and gazing

The ENJA15 ExperimentAugust 2015 to January 2016

● Each translator translated total 6 texts English-to-Japanese:1. from-scratch translation (T)2. translation dictation (D)3. MT post-editing (P)

● 39 native Japanese Translators ● 14 translators: 10+ years experience ● 17 translation students < 2 years experience● No experience in translation dictation

● 55 hours of English-to-Japanese user activity

● Data is publicly available free of charge

EN-to-JA Translation Duration

● Slower Translators are more likely to be more effective with D or P

Number of Insertions per PU (1000ms)

● Longer chunks of coherent insertions in translation dictation (D)

Average Production InEfficiency

● InEff = insertions+deletions/length of final translation

● D involves more deletions per translation than T

P02 P04 P18 P19 P22 P24 P280.000

0.500

1.000

1.500

2.000

2.500

T

D

Average Translation Duration per Texts

● Text 3: most difficult across all translation modes

● Less variance in Post-editing

Multilingual Translation Experiment (MLE)

> 150 hours of translation process data (T,P,E,D,C)774 translation sessions 108053 ST tokens, 122323 TT tokens

Average Translation Duration per Language

● EN-to-{DA,ES,DE} easier than EN-to-{JA,ZH,HI}

● Text 3: more difficult independent from TL

JTD16: Longitudinal Translation Study

● ENJA15: Translators had no experience with ASR and TD

– Some liked it others did not

● Can TD be learned within a few translation sessions and will TD translation speed increase?

● 7 translators (from the ENJA15 experiment) get used to TD over six successive days

● Translate 2 texts each day on 6 successive days within 3 weeks

– Text type: company mission statements

– Amounts to 7 * 12 = 84 translated texts

Average Translation Time per Text

Learning Effect in Translation Dictation

Post-experimental questionnaire

● With your experience from today's translation session: is TD easier than HT (regular ‘typing’)?

1: Yes, it is a lot easier,2: It is slightly easier3: about the same4: It is a lot more difficult than HT

● Translators did not perceive significant improvement over the 6 sessions.

Day1 Day2 Day3 Day4 Day5 Day60

1

2

3

4

5

P2

P4

P18

P19

P22

P24

P28

Conclusion

● Translation Dictation and ASR:

– novel method of Human-Machine Interaction in Translation

– quicker than from-scratch, approximately as efficient as PE

– no learning effect over 6 days

● Why do translators produce longer chunks in TD:

– concurrent reading ST and typing easier than TT speaking?

– speaking interferes with phonological loop to a larger extent than writing?

● Why is there no learning effect

– better (more professional) training required?

– maybe more fundamental things going on?

● Which texts are suited for dictation, post-editing, translation

– How are processes different/similar?