WMT24 Chat Task

This shared task will examine machine translation in the Chat domain.

© 2024. All rights reserved.

Welcome to the WMT 2024 Chat Shared Task!

Updates

March 15th, 2024

❗ Training data is available here.

❗ Please also register to the chat-shared-task google-group in order to be able to receive immediate updates announcements and ask us questions!

❗ Development sets along with baselines scores on them will be available soon!


Overview

Translating conversational text, in particular customer support chats, is an important and challenging application for machine translation technology. This type of content has so far not been extensively explored in prior MT research, largely due to the lack of publicly available data sets. Prior related work has mostly focused on movie subtitles and European Parliament speeches.
In contrast to the translation of the news stories, software manuals, biomedical text, etc. in which the text is carefully authored and well formated, chat conversations are less planned, more informal, and often ungrammatical. Further, such conversations are usually characterized by shorter and simpler sentences and contain more pronouns.
In effect, the task of translating chat conversations can be regarded as a two-in-one task, modelling both dialogue and translation at the same time.

Machine translation systems trained for chat conversations are expected to deal with the task’s inherent challenges and characteristics, such as (among others):

The primary goal of this Chat shared task is to encourage participants to train and test models specific for bilingual chat conversations in a corpus composed of original bilingual costumer support conversations.

This year we expanded the language pairs to en⇔de, en⇔fr, en⇔pt_br, en⇔ko and en⇔nl.

We encourage participants to use the bilingual context in the translation models submissions.

Have questions or suggestions? Feel free to Contact Us!

Chat Task Important Dates

  Date
Training set ready to download March 2024
Validation set ready to download May 2024
Test set ready to download June/July 2024
Submission deadline for Chat task July 2024
Paper submission deadline to WMT TBA around 12th August (follows EMNLP)
WMT Notification of acceptance TBA (follows EMNLP)
WMT Camera-ready deadline TBA around 23rd September (follows EMNLP)
Conference 12-13 November, 2024

Goals

The goals of chat translation shared task are to provide the common ground for:

Task Description

A critical challenge faced by international companies today is delivering customer support in several different languages. One solution to this challenge is centralizing support with English speaking agents and having a translation layer in the middle to translate from the customer’s language into the agent’s (English) and vice versa.

Data

The data used in this shared task is composed of genuine bilingual costumer support conversations. One of the main challenges of this domain is the lack of real bilingual training data available.

Please note, that all the data released for the WMT24 Chat Translation task is under the license of CC-BY-NC-4.0 and can be freely used for research purposes only. Please note that, as the license states, no commercial uses are permitted for this corpus. We just ask that you cite the WMT24 Chat Translation Task overview paper. Any other use is not permitted unless previous written authorization is given by Unbabel.

Datasets

The Training sets of all the language pairs are available in the github repository. The files contain the bilingual conversations by a customer and an agent in their original language. Here is an example of such a conversation:

source_language mt_language source_segment pe_segment translation_direction
fr en Bonjour je ne peut pas utiliser mes jetons accumuler pour acheter un livre audio Hello, I can’t use the tokens I accumulated to buy an audio book. customer
en fr Thank you for contacting #PRS_ORG#, it was my pleasure to assist you today. Merci d’avoir contacté #PRS_ORG#, ce fut un plaisir de vous aider aujourd’hui. agent
en fr I hope you have an excellent day. J’espère que vous passez une excellente journée. agent
en fr Please allow me a moment to verify the account. Veuillez m’accorder un moment pour vérifier le compte. agent
en fr I am sorry that you are experiencing this issue, I will do my best to assist you. Je suis désolé que vous rencontriez ce problème, je ferai de mon mieux pour vous aider. agent
en fr What is the error message or problem you are getting when trying to use your audio book credits? Quel est le message d’erreur ou le problème que vous rencontrez lorsque vous essayez d’utiliser vos crédits de livres audio ? agent
fr en Je ne peu pas effectuer l achat je peu juste le faire avec #PRS_ORG# ou par carte I am unable to make the purchase, I can only do it with #PRS_ORG# or by card. customer
en fr Are your credit s from an #PRS_ORG# subscription? Vos crédits proviennent-ils d’un abonnement #PRS_ORG# ? agent
fr en Oui Yes. customer
en fr I understand, at the moment we no longer work with #PRS_ORG#, they are not partnered with us anymore, probably that is the error, please let me confirm this information Je comprends, pour le moment nous ne travaillons plus avec #PRS_ORG#, ils ne sont plus en partenariat avec nous, c’est probablement la raison de l’erreur, laissez-moi confirmer ces informations agent
fr en Mais ça me met que j ai 13 jetons à utiliser But it shows that I have 13 tokens. customer
en fr I am confirming the information with my team, thanks for your patience Je confirme les informations avec mon équipe, merci pour votre patience agent



As you can see, the source sentences (i.e. source_segment) are in the original language of the speaker, i.e. French in the case of customer and English in the case of agent. And the translations (i.e. pe_segment). Moreover, since the data is anonymised, we have the entities replaced by the following special tokens:

Token Description
#NAME# Person’s names
#PRS_ORG# Products and Services, and Organizations
#ADDRESS# Address
#EMAIL# E-mail address
#IP# IP Address
#PASSWORD# Password
#PHONENUMBER# Phone number
#CREDITCARD# Credit card number
#URL# URL Address
#IBAN# IBAN number
#NUMBER# Any number (all digits)
#ALPHANUMERIC_ID# Any alphanumeric ID


Note that for training and validation purposes you can use the training data of the general task (including the data of the previous editions), the data of the other tracks (eg. biomedical) if you find them useful for this task, and the other corpora (either parallel or monolingual) that are publicly available for the research purposes, like most of the corpora available on OPUS, as well as the data of the previous edition of the Chat Translation Task.


Baseline Scores on DevSets

Baseline scores on Development sets will be available by May 2024.


Test Sets (Evaluation Data)

Test Sets will be available by June/July 2024.

Submission Format

TBD

Evaluation

The Systems’ performance will be evaluated along two domensions:

1) Human evaluation

2) Automatic evaluation

The human document-level evaluation will be performed only on the primary submission and will be used for the official rankings of the participating teams accounting for both directions. Automatic evaluation will be used as the secondary metric.


Paper Describing Your MT Systems

Participants are invited to submit a short paper (4 to 6 pages) to WMT describing their MT system. Information on how to submit is available here.
Please note that the shared task submission description papers are non-archival, and it is not mandatory to submit a paper if you do not want to.

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