Logo Lanfrica

sanusishafii989/Multilingual-Speech-to-Text

Domaine:

natural language processing

Type de record:

software
Créateur:
san
Hôte:
A powerful, multilingual speech-to-text application with advanced NLP analytics capabilities. Supports real-time recording, audio file upload, and comprehensive text analysis across Hausa, English, and Arabic — with a clean, modern UI featuring light and dark modes. # English Speech to Text NLP System A final year student project featuring an advanced NLP-based speech recognition system with a beautiful modern interface. ## 🧠 Project Overview This is a full-stack NLP application that converts English speech to text and provides comprehensive natural language processing analysis including: - **Speech Recognition** - Real-time voice-to-text conversion - **Sentiment Analysis** - Detect positive, negative, or neutral tone - **Keyword Extraction** - Identify important keywords with importance scores - **Text Statistics** - Word count, sentence count, average word length - **Text Summarization** - Auto-generate text summaries - **Named Entity Recognition** - Extract persons, organizations, locations - **Part-of-Speech Tagging** - Identify nouns, verbs, adjectives, etc. ## 📁 Project Structure ``` ENGLISH SPEECH TO TEXT/ ├── backend/ │ ├── app.py # Flask API with NLP processing │ └── requirements.txt # Python dependencies ├── frontend/ │ ├── public/ │ │ └── index.html # HTML template │ ├── src/ │ │ ├── App.js # React main component │ │ ├── index.js # React entry point │ │ └── index.css # Beautiful CSS styling │ └── package.json # Node.js dependencies └── README.md # This file ``` ## 🚀 Quick Start ### Option 1: Full Stack (Backend + Frontend) #### Backend Setup ```bash cd backend pip install -r requirements.txt python app.py ``` The backend runs on `localhost` #### Frontend Setup ```bash cd frontend npm install npm start ``` The frontend runs on `localhost` ### Option 2: Frontend Only (Demo Mode) The frontend works standalone in demo mode without the backend: - NLP analysis runs locally with basic processing - Speech recognition uses Web Speech API Simply open the frontend in a browser - it will work with limited NLP features. ## 🔧 Technology Stack ### Backend - **Python 3.8+** - **Flask** - Web framework - …