AI-Powered Lecture Transcription &
Summarization Tool
This project aims to create an AI-driven tool that provides real-time transcription and
summarization of lectures at Bahçeşehir University. This tool will help students focus more
on understanding content during lectures by automating note-taking and summarization.
The project will contribute to sustainability efforts at the university by reducing paper
waste, as well as enhancing accessibility for students by providing multi-language support
for diverse populations.
Project Title and Concept
Purpose
The purpose of this project is to develop an AI-powered transcription and summarization
tool that provides live transcriptions of lectures and automatically generates summaries.
This tool aims to support both students and professors in creating more efficient and
accessible educational experiences. It also aligns with Bahçeşehir University’s sustainability
goals by reducing the reliance on paper-based note-taking and supporting digital
transformation within the university.
Main Activities
1. Develop the AI algorithm for live transcription and summarization.
2. Integrate the tool with BAU’s existing platforms (Moodle and ItsLearning).
3. Provide multi-language support (Turkish, Arabic, English).
4. Create a mobile app and a web platform to enhance accessibility.
5. Conduct testing and refine the tool based on user feedback.
Duration
The project will span approximately 6 months, with the following timeline:
1. March - April: Development and setup of AI model, integration with BAU platforms.
2. May: Testing phase with selected courses.
3. June: Full implementation and official launch for students and faculty.
4. July - August: Feedback collection and refinements.
Relevance to THE Impact
This project directly aligns with the **THE Impact Rankings** by contributing to the
improvement of education quality and accessibility (SDG 4 - Quality Education). The AIpowered tool enhances lecture engagement by helping students focus on content rather
than writing, and by providing them with easily searchable transcriptions and summaries
after the lectures. Professors benefit from more effective use of their time by minimizing the
need to repeat explanations and helping students with diverse learning needs.
Relevance to UNSDGs
The project contributes to the following UNSDGs:
- **SDG 4: Quality Education** – Supports equitable access to learning resources by
providing real-time transcription and multi-language support.
- **SDG 11: Sustainable Cities & Communities** – Helps reduce unnecessary travel to
lectures by enabling remote learning.
- **SDG 13: Climate Action** – Reduces paper usage, helping the university move toward
more sustainable practices in education.
Project Management Plan
Timeframe
1. **March - April**: Development and initial integration of the tool.
2. **May**: Conduct pilot testing with select courses.
3. **June**: Official launch of the tool.
4. **July - August**: Collect feedback, refine the tool, and implement improvements.
Itemized Resources
1. **AI Speech-to-Text Software**: Needed for accurate live transcription.
2. **Cloud Storage**: To store and manage transcriptions and summaries.
3. **Mobile & Web Development**: For creating the platform and app.
4. **Training & Awareness Campaign**: For educating faculty and students on how to use
the tool.
Itemized Budget
| Expense
| Cost (TL) |
|----------------------------|------------|
| AI Speech-to-Text Software | 15,000 TL |
| Cloud Storage
| 8,000 TL |
| Mobile & Web Development | 12,000 TL |
| Training & Awareness Campaign| 5,000 TL |
Risks Plan
Potential risks and mitigation strategies include:
1. **Inaccurate transcription**: Continuous updates and improvements to the AI model to
enhance accuracy.
2. **Resistance to new technology**: Offering training sessions for faculty and students and
gathering feedback to make improvements.
3. **Privacy concerns**: Ensuring data is securely stored and access is restricted to
authorized users only.
Stakeholder Engagement
Key stakeholders include:
1. **Students**: The primary users of the tool.
2. **Professors**: Beneficiaries of the reduced workload and more efficient class
interactions.
3. **IT Department**: Responsible for integrating the tool into BAU’s platforms.
4. **University Administration**: Overseeing project implementation and securing funding
if necessary.
Legal Issues
Legal considerations include:
1. **Data privacy**: Compliance with GDPR and university data protection policies.
2. **Copyright**: Ensuring transcriptions and summaries do not infringe on any copyright
laws, especially for proprietary lecture content.
Action Plan
The action plan includes the following steps:
1. Finalizing project scope and objectives.
2. Building the AI model and integrating it with existing platforms.
3. Testing the tool with selected courses.
4. Gathering feedback and refining the tool for full-scale launch.
5. Launching the tool officially and promoting its use within the university.
Plan for Post-Project Period
After the project launch, we will focus on the following:
1. Gathering user feedback to refine and improve the system.
2. Continuously updating the AI model to improve accuracy and handle various accents and
environments.
3. Exploring opportunities for further integration into other university platforms or
expanding to other institutions.