MMehmet Ünlü
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Mehmet Ünlü

I study Electronics and Communication Engineering at ITU and build hands-on projects around forecasting, computer vision, and making data workflows faster.

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FlutterFirebaseAI ProductSpeech ProcessingMobile

AI-Powered Storytelling / Flutter App

Designed a Flutter and Firebase application concept that combines parent/child flows, media upload, subtitles, voice processing, and prompt-based AI generation.

GitHub

Roles

Parent / Child

Separated UX

Media

Video + Voice

Upload workflows

AI

Prompts

Generated content

Project Gallery

AI-Powered Storytelling / Flutter App
AI-Powered Storytelling / Flutter App screenshot 1
AI-Powered Storytelling / Flutter App screenshot 2
AI-Powered Storytelling / Flutter App screenshot 3
AI-Powered Storytelling / Flutter App screenshot 4

1/5

Problem

Family-oriented storytelling tools need safe flows for parents, understandable content for children, and flexible multimedia generation.

Challenge

The product concept has to coordinate mobile UX, Firebase-backed storage, uploaded media, prompt orchestration, and speech processing.

Architecture

How the pieces fit together.

Flutter handles the mobile interface, Firebase manages authentication and media state, and AI services provide story generation, subtitle handling, and voice processing.

Architecture View

System structure and decision flow

Flutter UX

Parent and child interaction surfaces.

Firebase

Authentication, storage, and media state.

Story Generation

Story, subtitle, and voice workflows.

Dataset / Inputs

  • User-provided video, subtitle selections, uploaded voice samples, and prompt inputs for story generation workflows.

Technical Decisions

  • Separate parent and child UX flows.
  • Use Firebase for authentication, storage, and app state.
  • Keep AI generation behind structured prompt orchestration.

Implementation Details

  • Flutter owns the cross-platform mobile interface.
  • Media upload flows collect video, subtitles, and voice inputs.
  • AI services generate story content and assist with speech-related features.

Metrics / Results

  • The app concept defines a practical architecture for AI-assisted multimedia storytelling with clear user roles and extensible content workflows.

Lessons Learned

  • AI product design needs role-aware guardrails.
  • Media workflows require clear progress and failure states.
  • Prompt systems benefit from structured user inputs.

Future Improvements

  • Add moderation and parent approval flows.
  • Introduce offline drafts and background upload retries.
  • Evaluate generated content quality with age-aware rubrics.