Tutorial: Simple Machine Translation: Yorùbá to English
Machine translation (MT) is a popular Natural Language Processing (NLP) task which involves the automatic translation of sentences from a source language to a target language. Machine translation models are very sensitive to the domain they were trained on which limit their generalization to multiple domains of interest like legal or medical domains. The problem is more severe in low-resource languages like Yorùbá where the most available datasets used for training are in the religious domain like JW300. How can we train MT models to generalize to multiple domains or quickly adapt to new domains of interest? In this challenge, you are provided with 10,000 Yorùbá to English parallel sentences sourced from multiple domains like news articles, ted talks, movie transcripts, radio transcripts, software localization texts, and other short articles curated from the web. Your task is to train a multi-domain MT model that will perform very well for practical use cases.
The goal of this challenge is to build a machine translation model to translate sentences from Yorùbá language to English language in several domains like news articles, daily conversations, spoken dialog transcripts and books. Your solution will be judged by how well your translation prediction is semantically similar to the reference translation.
The translation models developed will assist human translators in their jobs, help English speakers to have better communication with native speakers of Yorùbá, and improve the automatic translation of Yorùbá web pages to English language.
This competition is one of five NLP challenges we will be hosting on Zindi as part of AI4D’s ongoing African language NLP project, and is a continuation of the African language dataset challenges we hosted earlier this year. You can read more about the work here.
About Masakhane (masakhane.io)
Masakhane is the open research, participatory, grassroots NLP initiative for Africans by Africans, with the aim of putting African research in NLP on the map, by holistically tackling the problems facing society. Founded in 2019, Masakhane has since garnered over 400 researchers from over 30 African countries, published state of the art research for over 38 African languages at various venues, and has built a thriving community. Masakhane’s participatory approach has enabled researchers without formal scientific training to contribute data, evaluations and models to published research, by focusing on lowering the barriers of entry.
About AI4D-Africa; Artificial Intelligence for Development-Africa Network (ai4d.ai)
AI4D-Africa is a network of excellence in AI in sub-Saharan Africa. It is aimed at strengthening and developing community, scientific and technological excellence in a range of AI-related areas. It is composed of African Artificial Intelligence researchers, practitioners and policy makers.
This challenge is open to all.
Teams and collaboration
You may participate in competitions as an individual or in a team of up to four people. When creating a team, the team must have a total submission count less than or equal to the maximum allowable submissions as of the formation date. A team will be allowed the maximum number of submissions for the competition, minus the total number of submissions among team members at team formation. Prizes are transferred only to the individual players or to the team leader.
Multiple accounts per user are not permitted, and neither is collaboration or membership across multiple teams. Individuals and their submissions originating from multiple accounts will be immediately disqualified from the platform.
Code must not be shared privately outside of a team. Any code that is shared, must be made available to all competition participants through the platform. (i.e. on the discussion boards).
The Zindi user who sets up a team is the default Team Leader. The Team Leader can invite other data scientists to their team. Invited data scientists can accept or reject invitations. Until a second data scientist accepts an invitation to join a team, the data scientist who initiated a team remains an individual on the leaderboard. No additional members may be added to teams within the final 5 days of the competition or the last hour of a hackathon, unless otherwise stated in the competition rules
A team can be disbanded if it has not yet made a submission. Once a submission is made individual members cannot leave the team.
All members in the team receive points associated with their ranking in the competition and there is no split or division of the points between team members.
Datasets and packages
The solution must use publicly-available, open-source packages only. Your models should not use any of the metadata provided.
You may use only the datasets provided for this competition. Automated machine learning tools such as automl are not permitted. You may also use the JW300 parallel dataset to augment the data.
You may use pretrained models as long as they are openly available to everyone.
The data used in this competition is the sole property of Zindi and the competition host. You may not transmit, duplicate, publish, redistribute or otherwise provide or make available any competition data to any party not participating in the Competition (this includes uploading the data to any public site such as Kaggle or GitHub). You may upload, store and work with the data on any cloud platform such as Google Colab, AWS or similar, as long as 1) the data remains private and 2) doing so does not contravene Zindi’s rules of use.
You must notify Zindi immediately upon learning of any unauthorised transmission of or unauthorised access to the competition data, and work with Zindi to rectify any unauthorised transmission or access.
Your solution must not infringe the rights of any third party and you must be legally entitled to assign ownership of all rights of copyright in and to the winning solution code to Zindi.
Submissions and winning
You may make a maximum of 10 submissions per day.
You may only make a maximum of 300 submissions for this competition.
Before the end of the competition, you need to choose 2 submissions to be judged on for the private leaderboard. If you do not make a selection your 2 best public leaderboard submissions will be used to score on the private leaderboard.
Zindi maintains a public leaderboard and a private leaderboard for each competition. The Public Leaderboard includes approximately 50% of the test dataset. While the competition is open, the Public Leaderboard will rank the submitted solutions by the accuracy score they achieve. Upon close of the competition, the Private Leaderboard, which covers the other 50% of the test dataset, will be made public and will constitute the final ranking for the competition.
Note that to count, your submission must first pass processing. If your submission fails during the processing step, it will not be counted and not receive a score; nor will it count against your daily submission limit. If you encounter problems with your submission file, your best course of action is to ask for advice on the Competition’s discussion forum.
If you are in the top 20 at the time the leaderboard closes, we will email you to request your code. On receipt of email, you will have 48 hours to respond and submit your code following the submission guidelines detailed below. Failure to respond will result in disqualification.
If your solution places 1st, 2nd, or 3rd on the final leaderboard, you will be required to submit your winning solution code to us for verification, and you thereby agree to assign all worldwide rights of copyright in and to such winning solution to Zindi.
If two solutions earn identical scores on the leaderboard, the tiebreaker will be the date and time in which the submission was made (the earlier solution will win).
If the error metric requires probabilities to be submitted, do not set thresholds (or round your probabilities) to improve your place on the leaderboard. In order to ensure that the client receives the best solution Zindi will need the raw probabilities. This will allow the clients to set thresholds to their own needs.
The winners will be paid via bank transfer, PayPal, or other international money transfer platform. International transfer fees will be deducted from the total prize amount, unless the prize money is under $500, in which case the international transfer fees will be covered by Zindi. In all cases, the winners are responsible for any other fees applied by their own bank or other institution for receiving the prize money. All taxes imposed on prizes are the sole responsibility of the winners. The top 3 winners or team leaders will be required to present Zindi with proof of identification, proof of residence and a letter from your bank confirming your banking details. Winners will be paid in USD or the currency of the competition. If your account cannot receive US Dollars or the currency of the competition then your bank will need to provide proof of this and Zindi will try to accommodate this.
You acknowledge and agree that Zindi may, without any obligation to do so, remove or disqualify an individual, team, or account if Zindi believes that such individual, team, or account is in violation of these rules. Entry into this competition constitutes your acceptance of these official competition rules.
Zindi is committed to providing solutions of value to our clients and partners. To this end, we reserve the right to disqualify your submission on the grounds of usability or value. This includes but is not limited to the use of data leaks or any other practices that we deem to compromise the inherent value of your solution.
Zindi also reserves the right to disqualify you and/or your submissions from any competition if we believe that you violated the rules or violated the spirit of the competition or the platform in any other way. The disqualifications are irrespective of your position on the leaderboard and completely at the discretion of Zindi.
Please refer to the FAQs and Terms of Use for additional rules that may apply to this competition. We reserve the right to update these rules at any time.
Data standards:
Consequences of breaking any rules of the competition or submission guidelines:
Monitoring of submissions
The error metric for this competition is Rouge Score, ROUGE-N (N-gram) scoring (Rouge1), reporting the F-measure.
This error metric was implemented on 5 May 2021 and the leaderboard rescored.
The Recall-Oriented Understudy for Gisting Evaluation (ROUGE) scoring algorithm calculates the similarity between a candidate document and a collection of reference documents. Use the ROUGE score to evaluate the quality of document translation and summarization models [ref].
For every row in the dataset, submission files should contain 2 columns: ID and translation.
Your submission file should look like this:
ID English ID_AAAitMaH A Disaster Relief Committee... ID_AAKKdQwr May 22, 2018, at a....
1st Place: $1 000 USD
2nd Place: $600 USD
3rd Place: $400 USD
Competition closes on 30 May 2021.
Final submissions must be received by 11:59 PM GMT.
We reserve the right to update the contest timeline if necessary.
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