README.md

metadata

title: SpeakEdge - AI Sales Communication Coach
emoji: 🎯
colorFrom: purple
colorTo: blue
sdk: gradio
sdk_version: 5.49.1
app_file: app.py
pinned: false
license: mit
hardware: zero-gpu

🎯 SpeakEdge - Professional Communication Practice Platform

Master your sales conversations with AI-powered roleplay and comprehensive feedback

SpeakEdge is an advanced platform designed to help sales professionals practice and perfect their communication skills through realistic AI-powered roleplay scenarios. Get detailed feedback on your structure, delivery, and listening skills.

✨ Features

🎭 Realistic Roleplay Scenarios

Practice with 9 different sales situations:

• Cold call to a big shot CEO
• Cold call to the secretary of a big shot CEO
• Inbound customer discovery call
• Demo run through with a customer
• Negotiating pricing with a customer who wants unreasonable discounts
• Renewal or churn reduction with an angry customer
• Upselling to an existing customer
• Sharing update about a good week with your Head of Sales
• Sharing update about a poor week with your Head of Sales

🤖 AI-Powered Conversation

• Speech-to-Text (STT): Whisper large-v3 for accurate transcription
• Text-to-Speech (TTS): Parler-TTS with accent customization
• LLM: Mistral-7B-Instruct for dynamic, context-aware responses

📊 Comprehensive Feedback Analysis

Structure and Clarity

• Logical Flow: Ideas follow coherent sequence
• Simplicity of Language: Avoids jargon and complexity
• Conciseness: Eliminates unnecessary verbosity

Delivery and Presence

• Pace & Pauses: Optimal speaking speed (WPM)
• Confidence & Projection: Strong, definitive language
• Energy Level: Appropriate intensity for context

Listening and Interaction

• Active Listening: Questions and curiosity
• Acknowledgment: Validates others' points
• Reflection: Paraphrases and mirrors

📈 Advanced Metrics

• Words Per Minute (WPM)
• Filler words count and percentage
• Weak words detection
• Repetition analysis
• Unique AI insights (e.g., "23% of sentences started with 'And'")

🎨 Beautiful Dashboard

Professional, visual feedback dashboard with:

• Score breakdowns
• Color-coded performance indicators
• Actionable recommendations
• Unique pattern recognition

🚀 Quick Start

Prerequisites

• Python 3.9+
• CUDA-capable GPU (recommended) or CPU
• Hugging Face account with token

Installation

1. Clone the repository

git clone https://github.com/yourusername/SpeakEdge.git
cd SpeakEdge

2. Install dependencies

pip install -r requirements.txt

3. Set up Hugging Face token

export HF_TOKEN=your_hugging_face_token_here

Or create a .env file:

HF_TOKEN=your_hugging_face_token_here

4. Run the application

python app.py

The app will launch on http://localhost:7860

🌐 Hugging Face Spaces Deployment

This application is optimized for Hugging Face Spaces with Zero GPU (Dynamic H200 GPU Allocation).

Deploy to HF Spaces

1. Create a new Space

   • Go to Hugging Face Spaces
   • Click "Create new Space"
   • Choose Gradio as the SDK
   • Enable GPU (Zero GPU)

2. Upload files

   • Upload all Python files (app.py, models.py, scenarios.py, feedback_analyzer.py, dashboard.py, config.py)
   • Upload requirements.txt
   • Copy content from README_HF_SPACE.md to the Space's README.md

3. Set secrets (optional)

   • Go to Space settings
   • Add HF_TOKEN as a secret (optional but recommended for better rate limits)

4. Configure Space

   • The app will automatically start
   • Zero GPU will dynamically allocate H200 when needed

🎮 How to Use

1. Select Scenario: Choose the sales situation you want to practice
2. Customize Bot:
   • Select accent (American, British, Australian, Indian, Neutral)
   • Choose personality (Professional, Friendly, Skeptical, etc.)
   • Give your bot a name
3. Start Roleplay: Click "Start Roleplay" to begin
4. Engage: Speak naturally using your microphone
5. Interact: The AI bot will respond with voice and text
6. End Session: Click "End Roleplay" when finished
7. Review Feedback: Analyze your comprehensive performance dashboard

📁 Project Structure

SpeakEdge/
├── app.py                  # Main Gradio application
├── models.py              # STT, TTS, LLM model management
├── scenarios.py           # Scenario definitions and prompts
├── feedback_analyzer.py   # Feedback analysis logic
├── dashboard.py           # HTML dashboard generation
├── config.py              # Configuration settings
├── requirements.txt       # Python dependencies
├── README.md             # This file
└── README_HF_SPACE.md    # README for Hugging Face Spaces

🛠️ Technical Details

Models Used

Speech-to-Text

• Model: openai/whisper-large-v3
• Accuracy: High
• Latency: ~2-3 seconds per audio clip

Text-to-Speech

• Model: parler-tts/parler-tts-mini-v1
• Features: Multi-accent support
• Quality: Natural-sounding voices

Language Model

• Model: mistralai/Mistral-7B-Instruct-v0.3
• Purpose: Dynamic conversation & feedback generation
• Context: Last 6 messages for coherence
• Advantage: No approval needed, excellent performance

Performance Optimization

• Zero GPU Integration: Uses @spaces.GPU decorator for efficient GPU allocation
• Lazy Loading: Models load only when needed
• Mixed Precision: FP16 for faster inference on GPU
• Model Caching: Reuses loaded models across requests

🎯 Feedback Categories

Structure and Clarity (3 sub-aspects)

Analyzes logical flow, language simplicity, and conciseness of communication.

Delivery and Presence (3 sub-aspects)

Evaluates pace, confidence, and energy in speech delivery.

Listening and Interaction (3 sub-aspects)

Assesses active listening, acknowledgment, and adaptive responses.

💡 Unique Features

• Pattern Recognition: Identifies sentence starter patterns
• Repetition Detection: Highlights overused words
• Buzzword Tracking: Warns about jargon overuse
• Contextual Insights: AI-generated observations specific to your conversation
• Scenario-Specific Feedback: Tailored to the sales situation

🔧 Configuration

Edit config.py to customize:

• Model selections
• Generation parameters
• Audio settings
• Feedback thresholds

🤝 Contributing

Contributions are welcome! Please feel free to submit a Pull Request.

📄 License

This project is licensed under the MIT License.

🙏 Acknowledgments

• OpenAI Whisper for STT
• Parler-TTS for multi-accent TTS
• Mistral AI for Mistral-7B-Instruct model
• Hugging Face for hosting and Zero GPU infrastructure

📞 Support

For issues, questions, or suggestions, please open an issue on GitHub.

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Made with ❤️ for sales professionals looking to elevate their communication game