What Affects the Word Order of Target Language in Simultaneous Interpretation

Cai, Zhongxi; Ryu, Koichiro; Matsubara, Shigeki

doi:10.1109/ialp51396.2020.9310461

Cited by 4 publications

(2 citation statements)

References 10 publications

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“…In the translation (Ref), the word order was almost reversed from the English sentence, although the simultaneous interpreter successfully interpreted in the first-in-first-out manner. The example matched the word order patterns reported in Cai et al (2020), who found that simultaneous interpreters often preferred maintaining the word order in the original speech when interpreting nominal modifiers and dependent clauses.…”

Section: Word Ordersupporting

confidence: 76%

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Proceedings of the 18th International Conference on Spoken Language Translation (IWSLT 2021)

2021

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The evaluation campaign of the International Conference on Spoken Language Translation (IWSLT 2021) featured this year four shared tasks: (i) Simultaneous speech translation, (ii) Offline speech translation, (iii) Multilingual speech translation, (iv) Low-resource speech translation. A total of 22 teams participated in at least one of the tasks. This paper describes each shared task, data and evaluation metrics, and reports results of the received submissions.

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Section: Word Ordersupporting

confidence: 76%

“…Word order has also been intensively studied in the field. Recent research by Cai et al (2020) demonstrated a statistical study based on SIDB and compared word order between translation and SI.…”

Section: Translation Studiesmentioning

confidence: 99%

Proceedings of the 18th International Conference on Spoken Language Translation (IWSLT 2021)

2021

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Large-Scale English-Japanese Simultaneous Interpretation Corpus: Construction and Analyses with Sentence-Aligned Data

Doi¹,

Sudoh²,

Nakamura³

2021

Proceedings of the 18th International Conference on Spoken Language Translation (IWSLT 2021)

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This paper describes the construction of a new large-scale English-Japanese Simultaneous Interpretation (SI) corpus and presents the results of its analysis. A portion of the corpus contains SI data from three interpreters with different amounts of experience. Some of the SI data were manually aligned with the source speeches at the sentence level. Their latency, quality, and word order aspects were compared among the SI data themselves as well as against offline translations. The results showed that (1) interpreters with more experience controlled the latency and quality better, and (2) large latency hurt the SI quality.

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