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Are interpreters
and subtitlers
better respeakers?
Agnieszka Szarkowska & Łukasz Dutka
Agnieszka Chmiel, Agnieszka Lijewska, Krzysztof Krejtz, Krzysztof Marasek, Danijel Koržinek & Łukasz Brocki
Recruitment
• Interpreters
• Translators
• Controls
• (Subtitlers)
Respeaking
training
• 2-day
workshops
• Working
memory tests
• Proof-reading
tests
• Paraphrasing
tests
Respeaking
tests
• Intralingual
• Interlingual
Respeaking
quality analysis
• NER model
• Human raters
Data
triangulation
• Quality
• EEG
• Self-reported
cognitive load
• Eye-tracking
• Proof-reading
• Paraphrasing
• Ear-voice span
Respeaking test
Tasks in the respeaking test
Intralingual respeaking
–Polish to Polish
–Four 5-minute clips in randomised order
Interlingual respeaking
–English to Polish
–Speech by President Obama in Warsaw
Speech rate and number of speakers
Slow speech rate Fast speech rate
One speaker Speech News
Many speakers
Entertainment
show
Political chat show
58 participants
Mean age:
27.48 years (SD 5.71)
51 women, 7 men
22 Interpreters
12
Controls
10
Subtitlers
23 Translators
Professional experience
1 3 5 7 9 11 13
1-2 years
3-4 years
4+ years
Translators Interpreters
Measuring respeaking performance
1. NER model (NERstar)
–Accuracy rate = NER value
–Edition errors
–Recognition errors
–Reduction
2. Human rating on 1-5 scale
Rating
 Overall quality
 Fluency of delivery
 Pronunciation
 Punctuation
 Spoken to written language
 Accuracy of content
Are interpreters
better respeakers?
Interpreters had highest NER value
out of all the three groups
90 91 92 93 94 95
Interpreters
Translators
Controls
Interpreters had highest NER value
in all clips
90
91
92
93
94
95
Slow one-speaker Fast one-speaker Slow many speakers Fast many speakers
NER value
Interpreters Translators Controls
Interpreters had lowest reduction rates
0 5 10 15 20 25 30 35 40 45
Interpreters
Translators
Controls
Percentage of words omitted
(original speech vs. respoken text)
Interpreters were rated highest
in all categories
1
2
3
4
5
Fluency Pronunciation Punctuation Spoken to
written
Accuracy Overall
Interpreters Translators Controls
Interpreters were rated best
in interlingual respeaking
1 2 3 4 5
Interpreters
Translators
Controls
Are
better respeakers?
Subtitlers had higher NER value
than non-subtitlers
90 91 92 93 94 95
Subtitlers
Non-subtitlers
NER value
Subtitlers had an overall higher rating
than non-subtitlers
1 2 3 4 5
Subtitlers
Non-subtitlers
Overall rating of respeaking quality
Subtitlers were rated higher
in all intralingual tasks than non-subtitlers
1
2
3
4
5
Slow one-speaker Fast one-speaker Slow many speakers Fast many speakers
Overall rating of respeaking quality
Subtitlers Non-subtitlers
Subtitlers had highest scores
in the proof-reading test
0 20 40 60 80 100 120 140
Subtitlers
Interpreters
Controls
Proof-reading test score
Summary of all study results
 Interpreters and subtitlers achieved better results
as respeakers than other groups
– NER
– Rating
 NER and rating showed similar results
 Higher working memory capacity
correlated positively with high respeaking quality
 Interpreters had lower cognitive load during respeaking
 Interpreters were best in interlingual respeaking
 Translators/subtitlers gazed longest in the subtitle area and
achieved highest scores on the proof-reading test
Conclusions
 Interpreters as respeakers?
 Subtitlers as respeaking proof-readers?
 Respeaking as part of interpreting training
 Subtitling as part of respeaking training
 Train working memory capacity
Respeaking in Poland in 2016
Live events
–Intralingual
–Interlingual
–Online
On public television
–One-off events
–Respeaking tests
Challenges
 Legislation to increase subtitling quotas on TV
 Communicating with broadcasters
 Introducing respeaking as an independent
module at university
 Educating proof-readers for respeaking
 Educating the general public about the quality
of live subtitling
Our papers on respeaking
 Are interpreters better respeakers?
 Respeaking crisis points
 Ear-voice span and pauses in intra-
and interlingual respeaking
 Cognitive load in intralingual and interlingual respeaking
 Tapping the linguistic competence in respeaking:
comparing intralingual paraphrasing performed by
interpreters, translators and bilinguals
 Visual attention distribution in respeaking
– an eye tracking study
Acknowledgements
This study was supported
with the grant no. 013/11/B/HS2/02762
from the National Science Centre
for the years 2014-2017
KRZYSZTOF
KREJTZ
ŁUKASZ
BROCKI
AGNIESZKA
LIJEWSKA
AGNIESZKA
CHMIEL
KRZYSZTOF
MARASEK
DANIJEL
KORZINEK
Many thanks
to Juan Martínez Pérez
and Pablo Romero Fresco
for their support in this study
www.facebook.com/RespeakingProject
www.avt.ils.uw.edu.pl
a.szarkowska@uw.edu.pl
lukasz.dutka@uw.edu.pl

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Are interpreters and subtitlers better respeakers?

  • 1. Are interpreters and subtitlers better respeakers? Agnieszka Szarkowska & Łukasz Dutka Agnieszka Chmiel, Agnieszka Lijewska, Krzysztof Krejtz, Krzysztof Marasek, Danijel Koržinek & Łukasz Brocki
  • 2. Recruitment • Interpreters • Translators • Controls • (Subtitlers) Respeaking training • 2-day workshops • Working memory tests • Proof-reading tests • Paraphrasing tests Respeaking tests • Intralingual • Interlingual Respeaking quality analysis • NER model • Human raters Data triangulation • Quality • EEG • Self-reported cognitive load • Eye-tracking • Proof-reading • Paraphrasing • Ear-voice span
  • 4. Tasks in the respeaking test Intralingual respeaking –Polish to Polish –Four 5-minute clips in randomised order Interlingual respeaking –English to Polish –Speech by President Obama in Warsaw
  • 5. Speech rate and number of speakers Slow speech rate Fast speech rate One speaker Speech News Many speakers Entertainment show Political chat show
  • 6. 58 participants Mean age: 27.48 years (SD 5.71) 51 women, 7 men 22 Interpreters 12 Controls 10 Subtitlers 23 Translators
  • 7. Professional experience 1 3 5 7 9 11 13 1-2 years 3-4 years 4+ years Translators Interpreters
  • 8. Measuring respeaking performance 1. NER model (NERstar) –Accuracy rate = NER value –Edition errors –Recognition errors –Reduction 2. Human rating on 1-5 scale
  • 9. Rating  Overall quality  Fluency of delivery  Pronunciation  Punctuation  Spoken to written language  Accuracy of content
  • 11. Interpreters had highest NER value out of all the three groups 90 91 92 93 94 95 Interpreters Translators Controls
  • 12. Interpreters had highest NER value in all clips 90 91 92 93 94 95 Slow one-speaker Fast one-speaker Slow many speakers Fast many speakers NER value Interpreters Translators Controls
  • 13. Interpreters had lowest reduction rates 0 5 10 15 20 25 30 35 40 45 Interpreters Translators Controls Percentage of words omitted (original speech vs. respoken text)
  • 14. Interpreters were rated highest in all categories 1 2 3 4 5 Fluency Pronunciation Punctuation Spoken to written Accuracy Overall Interpreters Translators Controls
  • 15. Interpreters were rated best in interlingual respeaking 1 2 3 4 5 Interpreters Translators Controls
  • 17. Subtitlers had higher NER value than non-subtitlers 90 91 92 93 94 95 Subtitlers Non-subtitlers NER value
  • 18. Subtitlers had an overall higher rating than non-subtitlers 1 2 3 4 5 Subtitlers Non-subtitlers Overall rating of respeaking quality
  • 19. Subtitlers were rated higher in all intralingual tasks than non-subtitlers 1 2 3 4 5 Slow one-speaker Fast one-speaker Slow many speakers Fast many speakers Overall rating of respeaking quality Subtitlers Non-subtitlers
  • 20. Subtitlers had highest scores in the proof-reading test 0 20 40 60 80 100 120 140 Subtitlers Interpreters Controls Proof-reading test score
  • 21. Summary of all study results  Interpreters and subtitlers achieved better results as respeakers than other groups – NER – Rating  NER and rating showed similar results  Higher working memory capacity correlated positively with high respeaking quality  Interpreters had lower cognitive load during respeaking  Interpreters were best in interlingual respeaking  Translators/subtitlers gazed longest in the subtitle area and achieved highest scores on the proof-reading test
  • 22. Conclusions  Interpreters as respeakers?  Subtitlers as respeaking proof-readers?  Respeaking as part of interpreting training  Subtitling as part of respeaking training  Train working memory capacity
  • 23. Respeaking in Poland in 2016 Live events –Intralingual –Interlingual –Online On public television –One-off events –Respeaking tests
  • 24. Challenges  Legislation to increase subtitling quotas on TV  Communicating with broadcasters  Introducing respeaking as an independent module at university  Educating proof-readers for respeaking  Educating the general public about the quality of live subtitling
  • 25. Our papers on respeaking  Are interpreters better respeakers?  Respeaking crisis points  Ear-voice span and pauses in intra- and interlingual respeaking  Cognitive load in intralingual and interlingual respeaking  Tapping the linguistic competence in respeaking: comparing intralingual paraphrasing performed by interpreters, translators and bilinguals  Visual attention distribution in respeaking – an eye tracking study
  • 26. Acknowledgements This study was supported with the grant no. 013/11/B/HS2/02762 from the National Science Centre for the years 2014-2017 KRZYSZTOF KREJTZ ŁUKASZ BROCKI AGNIESZKA LIJEWSKA AGNIESZKA CHMIEL KRZYSZTOF MARASEK DANIJEL KORZINEK Many thanks to Juan Martínez Pérez and Pablo Romero Fresco for their support in this study