Collection of a Simultaneous Translation Corpus for Comparative Analysis

By Hiroaki Shimizu, Graham Neubig, Sakriani Watiasri Sakti, Tomoki Toda, Satoshi Nakamura. 2014

39 citations recorded by the source corpus.

This paper describes the collection of an English-Japanese/Japanese-English simultaneous interpretation corpus. There are two main features of the corpus. The first is that professional simultaneous interpreters with different amounts of experience cooperated with the collection. By comparing data from simultaneous interpretation of each interpreter, it is possible to compare better interpretations to those that are not as good. The second is that for part of our corpus there are already translation data available. This makes it possible to compare translation data with simultaneous interpretation data. We recorded the interpretations of lectures and news, and created time-aligned transcriptions. A total of 387k words of transcribed data were collected. The corpus will be helpful to analyze differences in interpretations styles and to construct simultaneous interpretation systems.

Subfields: Evaluation & Benchmarks, Machine Translation

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Evaluation & Benchmarks

1. Morgane Rivière
2. Hal Daumé Iii
3. Jordan L. Boyd-Graber
4. He He
5. Juan Pino
6. Ann Lee
7. Changhan Wang
8. Mary Williamson

In Machine Translation

1. Juan Pino
2. Changhan Wang
3. Anne Wu
4. Ann Lee
5. Jordan L. Boyd-Graber
6. He He
7. Hal Daumé Iii
8. Mary Williamson

Citations in the corpus

• VoxPopuli: A Large-Scale Multilingual Speech Corpus for Representation Learning, Semi-Supervised Learning and Interpretation (2021, background): “CIAIR (Tohyama et al., 2004) and STC (Shimizu et al., 2014) are simultaneous interpretation corpora between English and Japanese with a total of about 180 hours for the former, while the latter is currently unavailable for download.”
• CVSS Corpus and Massively Multilingual Speech-to-Speech Translation (2022, neutral): “, 2013) es→ en Telephone conversations (8 kHz) N/A 127 STC(2) (Shimizu et al., 2014) en→ ja TED talks Simultaneous interpretation 31 MaSS (Boito et al.”
• Syntax-based Rewriting for Simultaneous Machine Translation (2015, methodology): “…translations, a straightforward approach is to incorporate interpretation data into the learning of a machine translation (MT) system, because human interpreters use a variety of strategies (Shimizu et al., 2014; Camayd-Freixas, 2011; Tohyama and Matsubara, 2006) to fine-tune the word order.”
• Interpretese vs. Translationese: The Uniqueness of Human Strategies in Simultaneous Interpretation (2016, methodology): “Prior work studies simultaneous interpretation of Japanese ↔ English (Tohyama and Matsubara, 2006; Shimizu et al., 2014) and Spanish English (Sridhar et al., 2013).”