HelperAI solves the critical problem of language barriers and content accessibility in our globalized world. Many people struggle to understand complex documents, lengthy videos, and technical content—especially when it's in a foreign language or requires specialized knowledge.
HelperAI is an AI-powered productivity platform that breaks down these barriers by:
Document Intelligence: Transforms complex PDFs into clear, digestible summaries and explanations
Video Analysis: Transcribes and analyzes video content using Assembly AI and Gemini API, making hours of video accessible in minutes
Universal Translation: Converts all content into the user's preferred language with realistic AI voices via Murf.ai
Intelligent Chat: Provides instant explanations and answers on any topic with multilingual audio support
Unified Dashboard: Organizes all processed content with secure file handling and easy retrieval
The platform eliminates the time-consuming process of manually analyzing documents, watching lengthy videos, and struggling with language barriers—turning hours of work into minutes while making content accessible to global audiences regardless of their native language.
Demo video - https://drive.google.com/file/d/1Hs7ET4bpfOMrfs2JKrf2-63MamnG06zC/view?usp=sharing
Here is the code repo - https://github.com/saumya-14/HelperAi (give it a star)
How I Used Murf API
Murf API serves as the core voice generation engine in HelperAI, enabling seamless multilingual audio experiences across all platform features.
Primary Implementation:
- Multilingual Content Narration
Integrated Murf API to convert all AI-generated text responses into natural-sounding audio
Supports multiple languages and regional dialects for global accessibility
Users receive both text and audio versions of PDF summaries, video analyses, and chat responses
- Video Dubbing & Translation
After transcribing videos with Assembly AI and analyzing with Gemini API, I use Murf API to create dubbed versions
Automatically generates voiceovers in the user's preferred language
Maintains natural speech patterns and appropriate tone for different content types
- Dynamic Voice Selection
Implemented language-specific voice selection using Murf's diverse voice library
Automatically matches regional accents and dialects based on user preferences
Provides consistent voice experience across all generated content
Use Case & Impact
This solution is designed to help users effortlessly understand and consume PDF content in their preferred language through AI-powered translation and audio narration. It is especially beneficial for:
Students & Researchers: Quickly grasp lengthy academic papers, research articles, or eBooks in their native language without reading through dense text.
Professionals: Understand technical manuals, reports, or legal documents in unfamiliar languages with accurate audio explanations.
Visually Impaired Users: Gain access to written content in audio format, making information more accessible and inclusive.
Language Learners: Listen to translated PDFs to improve vocabulary and pronunciation in their target language.
Real-World Impact:
Reduces time spent reading and interpreting PDFs.
Breaks down language barriers by offering multilingual support.
Enhances accessibility for individuals with visual or reading impairments.
Streamlines document comprehension across education, legal, healthcare, and corporate domains.
By automating the explanation and dubbing of PDF content, this solution transforms static documents into dynamic, understandable, and inclusive learning tools.
Team name- Git push
member -Saumya Shrivastava
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