Meet the Winners: GIZ Agricultural Keyword Spotter Challenge Top 3 share their solutions
In Uganda, radio programs are a critical mode for sharing information and reaching out to rural communities. Farmers throughout Uganda, and across Africa, rely on radio programs in their local languages to learn more about agricultural practices and to obtain important market information.
While they are extremely valuable to their target listeners (agriculturalists), the content of these programs can also be important for researchers, government, and other decision makers as they provide an important source of information on the state of the agricultural sector. However the value to these other actors can be limited by the fact that this type of data is not easily monitored or analyzed, as the data is unstructured, often in local languages, and of varying sound quality.
The objective of this competition is to build a machine learning model to identify the agricultural keyword (which may be in English or Luganda) spoken in an audio clip. The keywords relate to crops, diseases, fertilizers, herbicides or other general agricultural topics.
This solution will help researchers from Makerere University who are developing a speech recognition model to automate the process of monitoring Luganda radio programs for agriculture-related information. This solution will enable more efficient monitoring and analysis of local language radio programs, and your work can possibly open doors for this type of natural language processing tasks in other local languages across Africa and across other sectors that use radio as a means of communication.
This challenge hosted in partnership with GIZ and the FAIR Forward initiative and the Artificial Intelligence for Development Africa(AI4D-Africa) Network.
About MUK researchers (twitter.com/air_lab_muk)
Makerere Artificial Intelligence (AI) Lab is an AI and Data Science research group based at the College of Computing and Information Sciences at Makerere University. The lab specializes in the application of artificial intelligence and data science - including, for example, methods from machine learning, computer vision and predictive analytics to problems in the developing world. This work is part of a research grant from Bill and Melinda Gates Foundation which has enabled us to build Artificial Intelligence models to mine Luganda data from local village radio stations to generate timely data on crop pests and diseases in Uganda. The results are now combined with images of diseased crops provided by local farmers and used to train machine learning models and ultimately provide a holistic crop and pest disease surveillance approach.
About FAIR Forward and GIZ (toolkit-digitalisierung.de/en/fair-forward)
The “FAIR Forward – Artificial Intelligence for all” initiative promotes a more open, inclusive and sustainable approach to AI on an international level. It is implemented by the Deutsche Gesellschaft für Internationale Zusammenarbeit (GIZ) on behalf of the German Federal Ministry for Economic Cooperation and Development (BMZ). FAIR Forward seeks to improve the foundations for AI innovation and policy in five partner countries: Rwanda, Uganda, Ghana, South Africa and India. Together with our partners, we focus on three areas of action: (1) strengthen local technical know-how on AI, (2) increase access to open AI training data, (3) develop policy frameworks ready for AI. For more information see https://toolkit-digitalisierung.de/en/fair-forward/.
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 and not restricted to any country.
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.
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 5 submissions per day. Your highest-scoring solution on the private leaderboard at the end of the competition will be the one by which you are judged.
Zindi maintains a public leaderboard and a private leaderboard for each competition. The Public Leaderboard includes approximately 25% 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 75% of the test dataset, will be made public and will constitute the final ranking for the competition.
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.
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.
Consequences of breaking any rules of the competition or submission guidelines:
Monitoring of submissions
The evaluation metric for this challenge is Log Loss.
Your submission should look like:
fn Pump Spinach abalimi audio_files/009WL0S.wav 0.73 0.19 0.01 audio_files/00AH117.wav 0.03 0.45 0.99
The values can be between 0 and 1. 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.
1st Place: $5 000 USD
2nd Place: $1 500 USD
3rd Place: $500 USD
Competition closes on 29 November 2020.
Final submissions must be received by 11:59 PM GMT.
We reserve the right to update the contest timeline if necessary.