VocalCheck

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  Landing page

🚀 Inspiration

Millions of professionals, students, and public speakers struggle to improve their presentation skills due to lack of real-time, objective feedback.

• 🎤 Speech Quality: Am I speaking clearly? Is my pacing correct?
  
• 🎥 Body Language: Am I making eye contact? What does my posture convey?
  
• 🧠 Overall Impact: How can I sound more confident and persuasive?

Traditional feedback is subjective, delayed, and limited, leading to inefficient practice and slow improvement.

💡 What It Does

Vocal Check is an AI-powered platform that analyzes both speech and body language from videos to deliver instant, multi-dimensional feedback.

🎤 Speech Analysis

• Detects filler words (um, uh, like, etc.)
• Measures pace and pause consistency
• Evaluates tone modulation and vocal variety
• Checks pronunciation clarity

🎥 Body Language Analysis

• Tracks posture and alignment
• Measures eye contact consistency
• Analyzes gestures and movement
• Detects facial expressions

🧠 AI-Powered Insights

• Personalized suggestions (Beginner → Advanced)
• Context-aware recommendations
• Goal-based improvement tips
• Text-to-Speech (TTS) summaries

📊 Detailed Reports

• JSON + human-readable reports
• Performance scoring system
• Confidence metrics and tracking
• Downloadable transcripts

🔥 Key Features

• ✅ Multi-Modal Analysis (Speech + Video + AI)
• ⚡ Instant Feedback from one upload
• 🎯 Skill-Level Based Training
• 🧪 Practice Mode with scoring
• 📂 PPT + Video Integration
• 👤 User Profiles & Progress Tracking
• 🔊 TTS Feedback Summaries
• 🔗 API-Ready Architecture

🛠️ How We Built It

Frontend

• HTML, CSS, JavaScript (Responsive UI)

Backend

• Python Flask (Modular architecture)

AI/ML Stack

• Google Gemini API → Intelligent feedback
  
• OpenAI Whisper → Speech-to-text
  
• Computer Vision → Body language analysis
  

Video Processing Pipeline

def process_video(video):
    audio = extract_audio(video)
    transcript = whisper.transcribe(audio)
    speech_metrics = analyze_speech(transcript)
    body_metrics = analyze_video_frames(video)
    insights = gemini.generate_feedback(speech_metrics, body_metrics)
    return insights


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## 🔥 NEXT STEP (IMPORTANT)

Replace these with your actual assets:

- `system-architecture.png`
- `pipeline.png`

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## 🎯 Want me to go one level higher?

I can generate for you:
- 🎨 **Actual system architecture diagram (ready image)**  
- 🔄 **Flowchart (clean + hackathon style)**  
- 📊 **UI mockups (dashboard, report screen)**  

Just say: **"generate images"** and I’ll create them 🚀

Built With

• advanced-cv-video-processing:-moviepy-with-ffmpeg-storage:-json-based-with-file-management-scalability:-rate-limiting
• async
• frontend:-javascript
• html/css-with-responsive-design-backend:-python-flask-with-modular-architecture-ai/ml:-google-gemini-api
• openai-whisper
• processing