1887
Volume 18, Issue 3
  • ISSN 1932-2798
  • E-ISSN: 1876-2700
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Abstract

Abstract

Facing a new technological turn, the field of interpreting is in great need of evidence on the effectiveness of computer-assisted interpreting. This study proposes a computer-assisted consecutive interpreting (CACI) mode incorporating speech recognition (SR) and machine translation (MT). First, the interpreter listens to the source speech and respeaks it into an SR system, creating an SR text which is then processed by an MT system. Second, the interpreter produces a target speech with reference to the SR and MT texts. Six students participated in training on CACI, after which they performed consecutive interpreting in both the conventional and the new mode. The study finds that CACI featured fewer pauses and reduced cognitive load. Moreover, the overall interpreting quality, especially the accuracy, was increased. The effectiveness of the new mode is found to be modulated by the interpreting direction.

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2022-12-05
2024-10-05
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References

  1. AIIC
    AIIC 2002 “Interpreter Workload Study – Full Report.” https://aiic.org/document/468/aiicwebzine_febmar2002_7_aiic_interpreter_wo. Last accessed21 June 2022.
  2. Arivazhagan, Naveen, Colin Cherry, Te, I., Wolfgang Macherey, Pallavi Baljekar, and George Foster
    2020 “Re-translation strategies for long form, simultaneous, spoken language translation.” In2020 IEEE International Conference on Acoustics, Speech, and Signal Processing Proceedings, Barcelona, May 4–8, 20201, 7919–7923. Piscataway: IEEE. 10.1109/ICASSP40776.2020.9054585
    https://doi.org/10.1109/ICASSP40776.2020.9054585 [Google Scholar]
  3. Azarmina, Pejman, and Paul Wallace
    2005 “Remote interpretation in medical encounters: A systematic review.” Journal of Telemedicine and Telecare111: 140–145. 10.1258/1357633053688679
    https://doi.org/10.1258/1357633053688679 [Google Scholar]
  4. Baddeley, Alan
    2012 “Working memory: Theories, models, and controversies.” Annual Review of Psychology631: 1–29. 10.1146/annurev‑psych‑120710‑100422
    https://doi.org/10.1146/annurev-psych-120710-100422 [Google Scholar]
  5. Braun, Sabine
    2013 “Keep your distance? Remote interpreting in legal proceedings: A critical assessment of a growing practice.” Interpreting15(2): 200–228. 10.1075/intp.15.2.03bra
    https://doi.org/10.1075/intp.15.2.03bra [Google Scholar]
  6. Chen, Sijia
    2017 “The construct of cognitive load in interpreting and its measurement.” Perspectives25(4): 640–657. 10.1080/0907676X.2016.1278026
    https://doi.org/10.1080/0907676X.2016.1278026 [Google Scholar]
  7. 2020 “The impact of directionality on the process and product in consecutive interpreting between Chinese and English: Evidence from pen recording and eye tracking.” JoSTrans: The Journal of Specialised Translation341: 100–117.
    [Google Scholar]
  8. Chmiel, Agnieszka
    2016 “Directionality and context effects in word translation tasks performed by conference interpreters.” Poznań Studies in Contemporary Linguistics52(2): 269–295. 10.1515/psicl‑2016‑0010
    https://doi.org/10.1515/psicl-2016-0010 [Google Scholar]
  9. Costa, Hernani, Gloria Corpas Pastor, and Isabel Durán Muñoz
    2018 “Assessing terminology management systems for interpreters.” InTrends in E-Tools and Resources for Translators and Interpreters, ed. byGloria Corpas Pastor and Isabel Durán-Muñoz, 57–84. Leiden: Brill. 10.1163/9789004351790
    https://doi.org/10.1163/9789004351790 [Google Scholar]
  10. Cunningham, Hetty, Linda F. Cushman, Cecilia Akuete-Penn, and Dodi D. Meyer
    2008 “Satisfaction with telephonic interpreters in pediatric care.” Journal of The National Medical Association100(4): 429–434. 10.1016/S0027‑9684(15)31277‑3
    https://doi.org/10.1016/S0027-9684(15)31277-3 [Google Scholar]
  11. Davitti, Elena, and Annalisa Sandrelli
    2020 “Embracing the complexity: A pilot study on interlingual respeaking.” Journal of Audiovisual Translation3(2): 103–139. 10.47476/jat.v3i2.2020.135
    https://doi.org/10.47476/jat.v3i2.2020.135 [Google Scholar]
  12. Dawson, Hayley
    2019 “Feasibility, quality and assessment of interlingual live subtitling: A pilot study.” Journal of Audiovisual Translation2(2): 36–56. 10.47476/jat.v2i2.72
    https://doi.org/10.47476/jat.v2i2.72 [Google Scholar]
  13. Dawson, Hayley, and Pablo Romero-Fresco
    2021 “Towards research-informed training in interlingual respeaking: An empirical approach.” The Interpreter and Translator Trainer15(1): 66–84. 10.1080/1750399X.2021.1880261
    https://doi.org/10.1080/1750399X.2021.1880261 [Google Scholar]
  14. de Jong, Nivja H., Rachel Groenhout, Rob Schoonen, and Jan H. Hulstijn
    2015 “Second language fluency: Speaking style or proficiency? Correcting measures of second language fluency for first language behavior.” Applied Psycholinguistics36(2): 223–243. 10.1017/S0142716413000210
    https://doi.org/10.1017/S0142716413000210 [Google Scholar]
  15. Defrancq, Bart, and Claudio Fantinuoli
    2021 “Automatic speech recognition in the booth: Assessment of system performance, interpreters’ performances and interactions in the context of numbers.” Target33(1): 73–102. 10.1075/target.19166.def
    https://doi.org/10.1075/target.19166.def [Google Scholar]
  16. Desmet, Bart, Mieke Vandierendonck, and Bart Defrancq
    2018 “Simultaneous interpretation of numbers and the impact of technological support.” InInterpreting and Technology, ed. byClaudio Fantinuoli, 13–27. Berlin: Language Science Press.
    [Google Scholar]
  17. Devaux, Jérôme
    2016 “When the role of the court interpreter intersects and interacts with new technologies.” InIntersect, Innovate, Interact. Ctis Occasional Papers, 71, ed. byPauline Henry-Tierney and Dinithi Karunanayake, 4–21. Manchester: Centre for Translation and Intercultural Studies.
    [Google Scholar]
  18. 2018 “Technologies and role-space: How videoconference interpreting affects the court interpreter’s perception of her role.” InInterpreting and Technology, ed. byClaudio Fantinuoli, 91–117. Berlin: Language Science Press.
    [Google Scholar]
  19. Fantinuoli, Claudio
    2018a “Computer-assisted interpreting: Challenges and future perspectives.” InTrends in E-tools and Resources for Translators and Interpreters, edited byIsabel Durán-Muñoz and Gloria Corpas Pastor, 153–174. Leiden: Brill. 10.1163/9789004351790_009
    https://doi.org/10.1163/9789004351790_009 [Google Scholar]
  20. 2018b “Interpreting and technology: The upcoming technological turn.” InInterpreting and Technology, ed. byClaudio Fantinuoli, 1–12. Berlin: Language Science Press.
    [Google Scholar]
  21. Fantinuoli, Claudio, and Bianca Prandi
    2021 “Towards the evaluation of automatic simultaneous speech translation from a communicative perspective.” InProceedings of the 18th International Conference on Spoken Language Translation (Iwslt 2021), 245–254. Bangkok: Association for Computational Linguistics. 10.18653/v1/2021.iwslt‑1.29
    https://doi.org/10.18653/v1/2021.iwslt-1.29 [Google Scholar]
  22. Gile, Daniel
    2009Basic Concepts and Models for Interpreter and Translator Training (Revised Edition). Amsterdam: John Benjamins. 10.1075/btl.8
    https://doi.org/10.1075/btl.8 [Google Scholar]
  23. Goldsmith, Joshua
    2018 “Tablet interpreting: Consecutive interpreting 2.0.” Translation and Interpreting Studies13(3): 342–365. 10.1075/tis.00020.gol
    https://doi.org/10.1075/tis.00020.gol [Google Scholar]
  24. Hamidi, Miriam, and Franz Pöchhacker
    2007 “Simultaneous consecutive interpreting: A new technique put to the test.” Meta52(2): 276–289. 10.7202/016070ar
    https://doi.org/10.7202/016070ar [Google Scholar]
  25. Han, Chao
    2015 “Investigating rater severity/leniency in interpreter performance testing: A multifaceted Rasch measurement approach.” Interpreting17(2): 255–283. 10.1075/intp.17.2.05han
    https://doi.org/10.1075/intp.17.2.05han [Google Scholar]
  26. Hart, Sandra G., and Lowell E. Staveland
    1988 “Development of NASA-TLX (Task Load Index): Results of empirical and theoretical research.” InHuman Mental Workload, ed. byPeter A. Hancock and Najmedin Meshkati, 139–183. Amsterdam: Elsevier. 10.1016/S0166‑4115(08)62386‑9
    https://doi.org/10.1016/S0166-4115(08)62386-9 [Google Scholar]
  27. Karimova, Sariya, Patrick Simianer, and Stefan Riezler
    2018 “A user-study on online adaptation of neural machine translation to human post-edits.” Machine Translation321: 309–324. 10.1007/s10590‑018‑9224‑8
    https://doi.org/10.1007/s10590-018-9224-8 [Google Scholar]
  28. Li, Ping, Fan Zhang, Anya Yu, and Xiaowei Zhao
    2020 “Language History Questionnaire (LHQ3): An enhanced tool for assessing multilingual experience.” Bilingualism: Language and Cognition23(5): 938–944. 10.1017/S1366728918001153
    https://doi.org/10.1017/S1366728918001153 [Google Scholar]
  29. Licoppe, Christian, Maud Verdier, and Claire-Antoine Veyrier
    2018 “Voice, power, and turn-taking in multilingual, consecutively interpreted courtroom proceedings with video links.” InHere or There: Research on Interpreting Via Video Link, ed. byJemina Napier, Robert Skinner and Sabine Braun, 299–322. Washington, DC: Gallaudet University Press. 10.2307/j.ctv2rh2bs3.14
    https://doi.org/10.2307/j.ctv2rh2bs3.14 [Google Scholar]
  30. Lin, Yumeng, Qianxi Lv, and Junying Liang
    2018 “Predicting fluency with language proficiency, working memory, and directionality in simultaneous interpreting.” Frontiers in Psychology91: 1–13. 10.3389/fpsyg.2018.01543
    https://doi.org/10.3389/fpsyg.2018.01543 [Google Scholar]
  31. Liu, Qun, and Xiaojun Zhang
    2015 “Machine translation: General.” InRoutledge Encyclopedia of Translation Technology, ed. bySin-wai Chan, 105–119. London: Routledge.
    [Google Scholar]
  32. Mellinger, Christopher D., and Thomas A. Hanson
    2018 “Interpreter traits and the relationship with technology and visibility.” Translation and Interpreting Studies13(3): 366–392. 10.1075/tis.00021.mel
    https://doi.org/10.1075/tis.00021.mel [Google Scholar]
  33. Najafian, Maryam, and Martin Russell
    2020 “Automatic accent identification as an analytical tool for accent robust automatic speech recognition.” Speech Communication1221: 44–55. 10.1016/j.specom.2020.05.003
    https://doi.org/10.1016/j.specom.2020.05.003 [Google Scholar]
  34. Nicodemus, Brenda, and Karen Emmorey
    2015 “Directionality in ASL-English interpreting: Accuracy and articulation quality in L1 and L2.” Interpreting17(2): 145–166. 10.1075/intp.17.2.01nic
    https://doi.org/10.1075/intp.17.2.01nic [Google Scholar]
  35. Orlando, Marc
    2014 “A study on the amenability of digital pen technology in a hybrid mode of interpreting: Consec-simul with notes.” Translation & Interpreting6(2): 39–54.
    [Google Scholar]
  36. Orlando, Marc, and Jim Hlavac
    2020 “Simultaneous-consecutive in interpreter training and interpreting practice: Use and perceptions of a hybrid mode.” The Interpreters’ Newsletter251: 1–17.
    [Google Scholar]
  37. Peris, Álvaro, Miguel Domingo, and Francisco Casacuberta
    2017 “Interactive neural machine translation.” Computer Speech & Language451: 201–220. 10.1016/j.csl.2016.12.003
    https://doi.org/10.1016/j.csl.2016.12.003 [Google Scholar]
  38. Pisani, Elisabetta, and Claudio Fantinuoli
    2021 “Measuring the impact of automatic speech recognition on number rendition in simultaneous interpreting.” InEmpirical Studies of Translation and Interpreting, ed. byCaiwen Wang and Binghan Zheng, 181–197. New York: Routledge. 10.4324/9781003017400‑14
    https://doi.org/10.4324/9781003017400-14 [Google Scholar]
  39. Pöchhacker, Franz
    2016Introducing Interpreting Studies (Second Edition). London: Routledge. 10.4324/9781315649573
    https://doi.org/10.4324/9781315649573 [Google Scholar]
  40. Pöchhacker, Franz, and Aline Remael
    2019 “New efforts? A competence-oriented task analysis of interlingual live subtitling.” Linguistica Antverpiensia181: 130–143. 10.52034/lanstts.v18i0.515
    https://doi.org/10.52034/lanstts.v18i0.515 [Google Scholar]
  41. Quené, Hugo, Ingrid Persoon, and Nivja de Jong
    2010 “Praat script syllable nuclei.”
    [Google Scholar]
  42. Rinne, Juha O., et al
    2000 “The translating brain: Cerebral activation patterns during simultaneous interpreting.” Neuroscience Letters294(2): 85–88. 10.1016/S0304‑3940(00)01540‑8
    https://doi.org/10.1016/S0304-3940(00)01540-8 [Google Scholar]
  43. Romero-Fresco, Pablo
    2011Subtitling through Speech Recognition: Respeaking. Manchester: Routledge.
    [Google Scholar]
  44. 2012 “Respeaking in translator training curricula: Present and future prospects.” The Interpreter and Translator Trainer6(1): 91–112. 10.1080/13556509.2012.10798831
    https://doi.org/10.1080/13556509.2012.10798831 [Google Scholar]
  45. Romero-Fresco, Pablo, and Carlo Eugeni
    2020 “Live subtitling through respeaking.” InThe Palgrave Handbook of Audiovisual Translation and Media Accessibility, ed. byŁukasz Bogucki and Mikołaj Deckert, 269–295. Cham: Palgrave. 10.1007/978‑3‑030‑42105‑2_14
    https://doi.org/10.1007/978-3-030-42105-2_14 [Google Scholar]
  46. Roziner, Ilan, and Miriam Shlesinger
    2010 “Much ado about something remote: Stress and performance in remote interpreting.” Interpreting12(2): 214–247. 10.1075/intp.12.2.05roz
    https://doi.org/10.1075/intp.12.2.05roz [Google Scholar]
  47. Seeber, Kilian G.
    2011 “Cognitive load in simultaneous interpreting: Existing theories – New models.” Interpreting13(2): 176–204. 10.1075/intp.13.2.02see
    https://doi.org/10.1075/intp.13.2.02see [Google Scholar]
  48. Tommola, Jorma, and Marketta Helevä
    1998 “Language direction and source text complexity: Effects on trainee performance in simultaneous interpreting.” InUnity in Diversity? Current Trends in Translation Studies, ed. byLynne Bowker, Michael Cronin, Dorothy Kenny and Jennifer Pearson, 177–186. Manchester: St. Jerome.
    [Google Scholar]
  49. Vieira, Lucas Nunes
    2019 “Post-editing of machine translation.” InThe Routledge Handbook of Translation and Technology, ed. byMinako O’Hagan, 319–335. London: Routledge. 10.4324/9781315311258‑19
    https://doi.org/10.4324/9781315311258-19 [Google Scholar]
  50. Wang, Xinyu, and Caiwen Wang
    2019 “Can computer-assisted interpreting tools assist interpreting?” Transletters. International Journal of Translation and Interpreting31: 109–139.
    [Google Scholar]
  51. Xiong, Hao, Ruiqing Zhang, Chuanqiang Zhang, Zhongjun He, Hua Wu, and Haifeng Wang
    2019 Dutongchuan: Context-Aware Translation Model for Simultaneous Interpreting. CitetononCRdoi:10.48550/arXiv.1907.12984
    https://doi.org/Cite to nonCR doi: 10.48550/arXiv.1907.12984 [Google Scholar]
  52. Yu, Dong, and Li Deng
    2015Automatic Speech Recognition: A Deep Learning Approach. London: Springer. 10.1007/978‑1‑4471‑5779‑3
    https://doi.org/10.1007/978-1-4471-5779-3 [Google Scholar]
  53. Yu, Wenting, and Vincent J. van Heuven
    2017 “Predicting judged fluency of consecutive interpreting from acoustic measures: Potential for automatic assessment and pedagogic implications.” Interpreting19(1): 47–68. 10.1075/intp.19.1.03yu
    https://doi.org/10.1075/intp.19.1.03yu [Google Scholar]
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