Why choose this project topic?
A study of classifying a bounded set of Yoruba service-request intents gives this topic a concrete purpose beyond simply adding an AI model. Comparing macro F1, intent confusion and unknown-intent rejection helps a student demonstrate capability, inspect failure cases and explain where human review or a simpler method remains necessary.
How effectively can low-resource yoruba intent recognition support classifying a bounded set of Yoruba service-request intents, evaluated using macro F1, intent confusion and unknown-intent rejection?
Choose a feasible licensed or synthetic dataset and available compute budget, then agree a narrow evaluation for classifying a bounded set of Yoruba service-request intents with your supervisor.
Proposed project objectives
- 01Define the task, evidence and evaluation assumptions for classifying a bounded set of Yoruba service-request intents.
- 02Use licensed or consented phrases reviewed by a competent speaker, compare lightweight models and report performance on unseen wording.
- 03Measure macro F1, intent confusion and unknown-intent rejection against a stated baseline and analyse failure cases.
A suggested research approach
Use licensed or consented phrases reviewed by a competent speaker, compare lightweight models and report performance on unseen wording. Check dataset permissions and keep evaluation examples separate from model development. Record model versions, prompts or training settings, then compare macro F1, intent confusion and unknown-intent rejection using repeatable runs and retain incorrect outputs for a transparent limitations discussion.
What you will need
- Licensed or consented Yoruba phrases
- Qualified language reviewer
- Local modelling environment
Keep your project scope clear
A small corpus cannot represent all dialects or infer a speaker's ethnicity. Generated project writing does not include a trained or deployed AI application.
Artificial Intelligence project chapter outline
Use this outline as a starting point. You can edit the chapter titles to match your department’s format during setup.
- Chapter 1Introduction
- Chapter 2Literature Review
- Chapter 3System Analysis and Design
- Chapter 4System Implementation and Testing
- Chapter 5Summary, Conclusion and Recommendations
Turn this topic into your own final year project.
Your title, department, research question and outline are ready. Add your institution, personalise the details and continue to your project workspace.
Generate the Complete Project Generation uses your word balance. Review the draft and supply your own verified research findings.