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  • Deep Learning
  • NLP

Telugu Question Answering System

A transformer-based QA system built for the morphologically rich Telugu language.

Overview

An Indic transformer is fine-tuned on the 82K-pair TeQuAD dataset, with morphology-aware answer refinement improving span alignment for Telugu's agglutinative structure. Input works through text, transliteration, file upload and speech, supported by in-place transliteration and a virtual Telugu phonetic keyboard.

Problem Statement

Question answering research is dominated by English. Telugu is agglutinative and morphologically rich, so answer spans extracted by English-trained approaches routinely cut words in the wrong place.

Proposed Solution

Fine-tune an Indic transformer on a large Telugu QA corpus and add a morphology-aware refinement stage that corrects span boundaries, with input methods built for how Telugu is actually typed.

Key Features

  • Indic Transformer Fine-Tuning

    Trained on the 82K-pair TeQuAD dataset.

  • Morphology-Aware Answer Refinement

    Improves span alignment for Telugu's agglutinative structure.

  • Multimodal Input

    Text, transliteration, file upload, and speech-based search.

  • Accessibility Tools

    In-place transliteration and a virtual Telugu phonetic keyboard.

Technologies Used

Deep Learning / NLP

  • IndicBERT / MuRIL
  • Hugging Face Transformers
  • PyTorch

Language tooling

  • Transliteration
  • Morphological analysis
  • Speech-to-text

Application

  • Flask / FastAPI
  • React
  • Virtual keyboard

Project Workflow

  1. 1

    Question input

    The question arrives as text, transliteration, file or speech.

  2. 2

    Encoding

    The Indic transformer encodes question and context.

  3. 3

    Span prediction

    The model locates the candidate answer span.

  4. 4

    Morphological refinement

    Span boundaries are corrected for Telugu morphology.

  5. 5

    Answer delivery

    The refined answer is returned to the user.

What You'll Receive

  • Complete, runnable source code with folder structure
  • Project report and technical documentation
  • Ready-to-present PPT content
  • Setup and installation walkthrough
  • Line-by-line project explanation session
  • Viva question bank with answers
  • Bug fixing and troubleshooting help
  • Post-delivery support after submission

Frequently Asked Questions

How much does this project cost?

Every project is quoted individually, because the price depends on the modules you need, your technology stack, your college's format and your deadline. Send us the project name on WhatsApp and we'll share a quote the same day.

Can the project be customised to my college requirements?

Yes. Share your guide's requirements, preferred technology stack and abstract format, and we adapt the modules, dataset or UI accordingly.

Will I be able to explain this project during my viva?

That is the point of the explanation session. We walk you through the architecture, every module, the flow of data and the results, and hand over a viva question bank with answers.

What if the project does not run on my laptop?

We help you with setup end to end — dependencies, environment, database and configuration — over chat or a call until it runs on your machine.

Do I get support after submission?

Yes. Post-delivery support is included, so you can come back for fixes, doubts or demo help even after the project is delivered.

Want This Project?

Get complete source code, documentation, PPT, explanation, and support.

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