---
title: "FINDINGS OF THE IWSLT 2023 EVALUATION — Agarwal 2023"
description: "This overview reports on the 2023 evaluation campaign of IWSLT, the yearly conference on spoken language translation (SLT)."
authors: ["Milind Agarwal", "Sweta Agrawal", "Antonios Anastasopoulos", "Luisa Bentivogli", "Ondřej Bojar", "Claudia Borg", "Marine Carpuat", "Roldano Cattoni", "Mauro Cettolo", "Mingda Chen", "William Chen", "Khalid Choukri", "Alexandra Chronopoulou", "Anna Currey", "Thierry Declerck", "Qianqian Dong", "Kevin Duh", "Yannick Estève", "Marcello Federico", "Souhir Gahbiche", "Barry Haddow", "Benjamin Hsu", "Phu Mon Htut", "Hirofumi Inaguma", "Dávid Javorský", "John Judge", "Yasumasa Kano", "Tom Ko", "Rishu Kumar", "Pengwei Li", "Xutai Ma", "Prashant Mathur", "Evgeny Matusov", "Paul McNamee", "John P. McCrae", "Kenton Murray", "Maria Nadejde", "Satoshi Nakamura", "Matteo Negri", "Ha Nguyen", "Jan Niehues", "Xing Niu", "Atul Kr. Ojha", "John E. Ortega", "Proyag Pal", "Juan Pino", "Lonneke van der Plas", "Peter Polák", "Elijah Rippeth", "Elizabeth Salesky", "Jiatong Shi", "Matthias Sperber", "Sebastian Stüker", "Katsuhito Sudoh", "Yun Tang", "Brian Thompson", "Kevin Tran", "Marco Turchi", "Alex Waibel", "Mingxuan Wang", "Shinji Watanabe", "Rodolfo Zevallos"]
year: 2023
venue: "Proceedings of the 20th International Conference on Spoken Language Translation (IWSLT 2023)"
source: "https://aclanthology.org/2023.iwslt-1.1/"
doi: "10.18653/v1/2023.iwslt-1.1"
licence: "CC BY 4.0 (ACL Anthology)"
licence_url: "https://creativecommons.org/licenses/by/4.0/"
summary_licence: "Elamur Cosmic License"
canonical: "https://research.elamur.ai/free/papers/agarwal-2023-findings-iwslt-2023-evaluation-campaign/"
---
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# FINDINGS OF THE IWSLT 2023 EVALUATION CAMPAIGN

**Authors:** Milind Agarwal, [Sweta Agrawal](https://md.research.elamur.ai/free/authors/sweta-agrawal/), [Antonios Anastasopoulos](https://md.research.elamur.ai/free/authors/antonios-anastasopoulos/), [Luisa Bentivogli](https://md.research.elamur.ai/free/authors/luisa-bentivogli/), [Ondřej Bojar](https://md.research.elamur.ai/free/authors/ondrej-bojar/), [Claudia Borg](https://md.research.elamur.ai/free/authors/claudia-borg/), [Marine Carpuat](https://md.research.elamur.ai/free/authors/marine-carpuat/), [Roldano Cattoni](https://md.research.elamur.ai/free/authors/roldano-cattoni/), [Mauro Cettolo](https://md.research.elamur.ai/free/authors/mauro-cettolo/), [Mingda Chen](https://md.research.elamur.ai/free/authors/mingda-chen/), William Chen, [Khalid Choukri](https://md.research.elamur.ai/free/authors/khalid-choukri/) et al. (62 authors) · **Year:** 2023 · **Venue:** Proceedings of the 20th International Conference on Spoken Language Translation (IWSLT 2023) · **Licence:** [CC BY 4.0 (ACL Anthology)](https://creativecommons.org/licenses/by/4.0/)

**Links:** [Publisher's page](https://aclanthology.org/2023.iwslt-1.1/) · [PDF](https://aclanthology.org/2023.iwslt-1.1.pdf) · [DOI 10.18653/v1/2023.iwslt-1.1](https://doi.org/10.18653/v1/2023.iwslt-1.1) · [OpenAlex](https://openalex.org/W4385570170)

**Citations:** 57 citations (openalex-snapshot · 2026-10-14) · [96](#cited-by) in our library, of the 140673 papers whose bibliographies we read

## Summary
This overview reports on the 2023 evaluation campaign of IWSLT, the yearly conference on spoken language translation (SLT). Organizers from industry and academia ran nine shared tasks, each with its own data, metrics and analysis of submissions. The tasks were offline and simultaneous speech translation, automatic subtitling, automatic dubbing, speech-to-speech translation, multilingual SLT, dialect SLT, low-resource SLT and formality control. The offline track compared cascade (ASR+MT) and end-to-end systems under three training conditions. It also added harder test material beyond TED talks: ACL 2022 paper presentations and EPTV press conferences and interviews, which contain spontaneous speech, accents and multiple speakers. Ranking used BLEU and COMET, plus human evaluation of each team's best system. In the dubbing task, judges preferred the unconstrained HW-TSC system over all baselines. However, every dubbed video still showed much worse lip-sync than the originals. The paper serves as a benchmark snapshot of SLT and shows that realistic, noisy and low-resource conditions remain challenging.

## Key points
- The campaign received 38 submissions from 31 teams across 9 shared tasks.
- The offline track covered English→German/Japanese/Chinese with three training conditions: constrained, constrained+LLM and unconstrained. The en-de test set combined 42 new TED talks, 5 ACL presentations and 10 EPTV videos.
- The low-resource track covered six language pairs: Irish→English, Marathi→Hindi, Maltese→English, Pashto→French, Tamasheq→French and Quechua→Spanish. The dialect track covered Tunisian Arabic→English.
- In the German→English dubbing task, HW-TSC won with a MOS of 3.77. The baselines scored 3.16 (Text2Phone), 3.33 (Interleaved) and 3.43 (Factored).
- Lip-sync error (LSE-D) was about 7.4–7.7 for original videos versus roughly 11.6–13.3 for dubbed outputs. Annotators also showed personal biases for or against dubbing, with per-annotator MOS ranging from 3.07 to 3.74.

*Our summary of the paper, in our own words — not its text. The work belongs to its authors; read it at the links above.*

Fields: [Linguistics & languages](https://md.research.elamur.ai/free/shelves/linguistics/) · [Machine translation](https://md.research.elamur.ai/free/shelves/machine-translation/)

## Cited by

Cited by

96 papers of our library cite it (of the 140673 whose bibliographies we read); 4 of them have a page here, 92 not yet.

- [Seamless: Multilingual Expressive and Streaming Speech Translation](https://md.research.elamur.ai/free/papers/communication-2023-seamless-multilingual-expressive-streaming-speech/)
- [SeamlessM4T: Massively Multilingual & Multimodal Machine Translation](https://md.research.elamur.ai/free/papers/communication-2023-seamlessm4t-massively-multilingual-multimodal-machine/)
- [Team QUESPA System Submission for the IWSLT 2026 Dialectal and Low-resource Speech Translation Task](https://md.research.elamur.ai/free/papers/ortega-2026-team-quespa-system-submission-iwslt/)
- [The CUHKSZ System for the IWSLT 2026 Low-Resource Speech-to-Text Task](https://md.research.elamur.ai/free/papers/sun-2026-cuhksz-system-iwslt-2026-low/)

## Cite

The paper itself, not this page. BibTeX from the library's record of the work.

```bibtex
@inproceedings{agarwal2023findings,
  title = {{FINDINGS OF THE IWSLT 2023 EVALUATION CAMPAIGN}},
  author = {Agarwal, Milind and Agrawal, Sweta and Anastasopoulos, Antonios and Bentivogli, Luisa and Bojar, Ondřej and Borg, Claudia and Carpuat, Marine and Cattoni, Roldano and Cettolo, Mauro and Chen, Mingda and Chen, William and Choukri, Khalid and Chronopoulou, Alexandra and Currey, Anna and Declerck, Thierry and Dong, Qianqian and Duh, Kevin and Estève, Yannick and Federico, Marcello and Gahbiche, Souhir and Haddow, Barry and Hsu, Benjamin and Htut, Phu Mon and Inaguma, Hirofumi and Javorský, Dávid and Judge, John and Kano, Yasumasa and Ko, Tom and Kumar, Rishu and Li, Pengwei and Ma, Xutai and Mathur, Prashant and Matusov, Evgeny and McNamee, Paul and McCrae, John P. and Murray, Kenton and Nadejde, Maria and Nakamura, Satoshi and Negri, Matteo and Nguyen, Ha and Niehues, Jan and Niu, Xing and Ojha, Atul Kr. and Ortega, John E. and Pal, Proyag and Pino, Juan and Plas, Lonneke van der and Polák, Peter and Rippeth, Elijah and Salesky, Elizabeth and Shi, Jiatong and Sperber, Matthias and Stüker, Sebastian and Sudoh, Katsuhito and Tang, Yun and Thompson, Brian and Tran, Kevin and Turchi, Marco and Waibel, Alex and Wang, Mingxuan and Watanabe, Shinji and Zevallos, Rodolfo},
  booktitle = {Proceedings of the 20th International Conference on Spoken Language Translation (IWSLT 2023)},
  year = {2023},
  doi = {10.18653/v1/2023.iwslt-1.1},
  url = {https://doi.org/10.18653/v1/2023.iwslt-1.1}
}
```

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