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	---
	title: Beta
	emoji: 🐢
	colorFrom: blue
	colorTo: yellow
	sdk: static
	pinned: true
	license: mpl-2.0
	short_description: চা খাবা?
	---
	<div align="center">
	<img src="https://cdn-avatars.huggingface.co/v1/production/uploads/67497128927b345d1345e9de/69fZeWPoXB20L7do9nZDY.png" width="300" alt="Shôbdhonic Logo">

	# শব্দনিক \| Shôbdhonic

	### বাংলা NLP-এর নতুন যুগ
	"ভাষাকে জানো, AI-কে চেনো!"
	(Unlock Bangla's Future with AI)

	[![Website](https://img.shields.io/badge/Explore-Shobdhonic.com-6A5ACD?style=for-the-badge&logo=google-chrome)](https://shobdhonic.com)
	[![Discord](https://img.shields.io/badge/Chat_on-Discord-5865F2?style=for-the-badge&logo=discord)](https://discord.gg/shobdhonic)
	[![Twitter](https://img.shields.io/badge/Follow-@Shobdhonic-FF69B4?style=for-the-badge&logo=twitter)](https://twitter.com/Shobdhonic)
	[![Telegram](https://img.shields.io/badge/Join-Telegram-26A5E4?style=for-the-badge&logo=telegram)](https://t.me/Shobdhonic)
	[![GitHub](https://img.shields.io/badge/Star_on-GitHub-181717?style=for-the-badge&logo=github)](https://github.com/Shobdhonic)
	[![HuggingFace](https://img.shields.io/badge/Models-HuggingFace-FFD21E?style=for-the-badge&logo=huggingface)](https://huggingface.co/Shobdhonic)
	</div>

	---

	## 🚀 Why Shôbdhonic?
	A next-gen Bangla NLP platform built for:
	- 🔥 Gen-Z Creators: Meme generators, slang translators, TikTok/Reels integrations
	- 🏢 Enterprises: Sentiment analysis, fraud detection, document processing
	- 🇧🇩 Cultural Preservation: Digitize literature, dialects, and oral histories
	- 🧠 Research: Advanced Bangla language models, transformer architectures, and fine-tuning pipelines
	- 🌐 Web3: Blockchain integration for digital Bangla content authentication

	---

	## ✨ Key Features

	\| Category \| Tools \|
	\|-----------------------\|------------------------------------------------------------------------------------\|
	\| Gen-Z Playground \| `MemeGPT` • `Slang Translator` • `AI Rap Generator` • `Voice Filters` • `TikTok Content API` \|
	\| Enterprise NLP \| `Legal Doc Analyzer` • `News Sentiment API` • `Plagiarism Checker` • `Customer Service Bot` • `Bangla Data OCR` \|
	\| Voice Lab \| `Celebrity Voice Cloning` • `Regional Accent TTS` • `Audio Transcription` • `Dialect Analysis` • `Emotion Detection` \|
	\| Real-Time AI \| `Trend Predictor` • `Social Media Pulse` • `Ittefaq News Scanner` • `Market Sentiment Analysis` • `Election Opinion Tracker` \|
	\| Academia \| `Literature Analysis` • `Academic Paper Assistant` • `Educational Content Generator` • `Bangla Research Corpus` \|
	\| Security Suite \| `Bangla Fraud Detection` • `Phishing Text Analysis` • `Disinformation Tracker` • `Financial Alert System` \|

	---

	## 🎯 Core Technologies

	### Models Architecture
	- ShobdhoBERT: Transformer-based model trained on 5TB of Bangla text corpus
	- ShobdhoGPT-3.5: GPT-based generative model fine-tuned on diverse Bangla content
	- DialectDiffusion: Voice synthesis specialized for regional Bangla dialects
	- BanglaLLM-7B: Large Language Model optimized for Bangla instruction following
	- Multimodal-Bangla: Vision-language model for Bangla image-text understanding

	### Data Processing Pipeline
	- Proprietary text normalization for Bangla script variations
	- Context-aware slang detection and interpretation
	- Real-time news corpus analysis with automated categorization
	- Specialized tokenization for Bangla script with compound word handling
	- Advanced sentiment analysis for cultural nuances

	---

	## 🎨 Brand Identity
	### Colors
	\| Role \| Hex \| Preview \|
	\|---------------\|-----------\|------------------------\|
	\| Primary \| `#6A5ACD` \| ![#6A5ACD](https://placehold.co/50x30/6A5ACD/6A5ACD.png) \|
	\| Secondary \| `#FF69B4` \| ![#FF69B4](https://placehold.co/50x30/FF69B4/FF69B4.png) \|
	\| Accent \| `#00FFE0` \| ![#00FFE0](https://placehold.co/50x30/00FFE0/00FFE0.png) \|
	\| Dark Mode \| `#1A1A2E` \| ![#1A1A2E](https://placehold.co/50x30/1A1A2E/1A1A2E.png) \|
	\| Light Mode \| `#F5F5F7` \| ![#F5F5F7](https://placehold.co/50x30/F5F5F7/F5F5F7.png) \|

	### Mascot
	বর্গী বট (Borgi Bot) – Our street-smart AI mascot for Gen-Z campaigns:
	![Borgi Bot](https://png.pngtree.com/png-vector/20220624/ourmid/pngtree-chicken-logo-vector-illustration-template-vintage-design-meat-vector-png-image_37354522.png)

	---

	## ⚡ Quick Start
	### Prerequisites
	- Python 3.10+ / Node.js 18+
	- Hugging Face API Key (Register [here](https://huggingface.co/Shobdhonic))
	- Docker (optional, for containerized deployment)
	- GPU acceleration (recommended for model training/inference)

	### Installation

	```bash
	# Clone repo
	git clone https://github.com/Shobdhonic/core-engine.git
	cd core-engine

	# Create virtual environment
	python -m venv shobdhonic-env
	source shobdhonic-env/bin/activate # On Windows: shobdhonic-env\Scripts\activate

	# Install dependencies (Python)
	pip install -r requirements.txt

	# Or for Node.js
	npm install

	# Set up environment variables
	cp .env.example .env
	# Edit .env with your API keys
	```

	### Docker Setup
	```bash
	# Build the Docker image
	docker build -t shobdhonic:latest .

	# Run the container
	docker run -p 8000:8000 -v $(pwd):/app --env-file .env shobdhonic:latest
	```

	### Generate Your First Meme
	```python
	from shobdhonic import MemeMaster

	# Initialize with your API key
	meme_api = MemeMaster(api_key="your_api_key_here")

	# Create a meme with custom text and template
	meme = meme_api.create(
	text="একটা চা আর হয়না? ☕",
	template="cha_kaku",
	style="viral", # Options: viral, minimal, dramatic, retro
	font="bangla_classic",
	format="jpg" # Options: jpg, png, gif, mp4
	)

	# Save the meme
	meme.download("output/cha_kaku_meme.jpg")

	# Share directly to social media
	meme.share(platform="facebook") # Options: facebook, twitter, instagram, whatsapp
	```

	### Advanced Voice Cloning
	```python
	from shobdhonic import VoiceForge
	import numpy as np

	# Initialize voice engine
	voice_api = VoiceForge(api_key="your_api_key_here")

	# Clone a voice with emotion parameters
	voice = voice_api.clone(
	target_voice="bappa_sir", # Popular Bangla YouTuber
	text="ভাই, লাইক আর সাবস্ক্রাইব মনে হয়না!",
	emotion="excited", # Options: neutral, sad, excited, angry, persuasive
	dialect="dhaka", # Options: dhaka, chittagong, sylhet, rajshahi, khulna, barishal
	speed=1.2, # Playback speed multiplier (0.5 - 2.0)
	pitch_shift=0.3 # Adjust pitch (-1.0 to 1.0)
	)

	# Play the generated audio
	voice.play()

	# Save to file
	voice.save("output/bappa_youtube_promo.mp3")

	# Get waveform data for further processing
	waveform = voice.get_waveform()
	frequencies = np.fft.fft(waveform)
	```

	### News Sentiment Analysis
	```python
	from shobdhonic import NewsAnalyzer
	import pandas as pd
	import matplotlib.pyplot as plt

	# Initialize news analyzer
	news_api = NewsAnalyzer(api_key="your_api_key_here")

	# Analyze recent articles
	results = news_api.analyze(
	source="prothom_alo", # Options: prothom_alo, ittefaq, bangla_tribune, bbc_bangla
	category="politics", # Options: politics, business, sports, entertainment, tech
	date_range="last_7_days", # Options: today, last_24h, last_7_days, last_30_days, custom
	sample_size=100 # Number of articles to analyze
	)

	# Get sentiment breakdown
	sentiment_df = pd.DataFrame(results.sentiment_data)

	# Plot results
	plt.figure(figsize=(10, 6))
	plt.bar(sentiment_df['sentiment'], sentiment_df['percentage'])
	plt.title('Political News Sentiment Analysis')
	plt.xlabel('Sentiment')
	plt.ylabel('Percentage (%)')
	plt.savefig('output/sentiment_analysis.png')
	```

	### Enterprise Document Processing
	```python
	from shobdhonic import DocumentProcessor
	from shobdhonic.security import SensitiveDataDetector

	# Initialize document processor
	doc_api = DocumentProcessor(api_key="your_api_key_here")

	# Process legal document
	processed_doc = doc_api.process(
	file_path="contracts/agreement.pdf",
	tasks=[
	"summarize", # Create executive summary
	"extract_entities", # Find people, organizations, dates
	"identify_clauses", # Detect important legal clauses
	"risk_assessment" # Flag potentially problematic terms
	],
	output_format="json"
	)

	# Check for sensitive information
	sensitive_detector = SensitiveDataDetector()
	security_scan = sensitive_detector.scan(processed_doc.raw_text)

	if security_scan.has_sensitive_data:
	print(f"WARNING: Found {len(security_scan.findings)} instances of sensitive data")
	for finding in security_scan.findings:
	print(f"- {finding.type}: {finding.severity} risk level")

	# Export processed results
	processed_doc.export(
	output_path="output/processed_contract.json",
	include_metadata=True,
	redact_sensitive=True
	)
	```

	---

	## 🔋 Core Modules

	### Text Processing
	- `shobdhonic.tokenizer`: Advanced Bangla tokenization
	- `shobdhonic.transformer`: Pre-trained transformer models
	- `shobdhonic.nlp`: Natural language processing utilities
	- `shobdhonic.generator`: Text generation capabilities
	- `shobdhonic.translator`: Cross-language translation services

	### Audio & Speech
	- `shobdhonic.voice`: Text-to-speech and speech-to-text
	- `shobdhonic.audio`: Audio processing utilities
	- `shobdhonic.dialect`: Regional dialect processing

	### Media & Content
	- `shobdhonic.meme`: Meme generation engine
	- `shobdhonic.social`: Social media integration
	- `shobdhonic.content`: Content creation assistants
	- `shobdhonic.video`: Video generation and editing

	### Analysis & Intelligence
	- `shobdhonic.sentiment`: Sentiment analysis tools
	- `shobdhonic.analytics`: Usage statistics and reporting
	- `shobdhonic.trends`: Trend detection and prediction

	### Security & Enterprise
	- `shobdhonic.security`: Security and compliance tools
	- `shobdhonic.enterprise`: Enterprise integration utilities
	- `shobdhonic.docs`: Document processing pipeline

	---

	## 📈 Performance Benchmarks

	\| Task \| Shôbdhonic \| Other Bangla NLP \| Improvement \|
	\|------------------------------\|-----------------\|----------------------\|-----------------\|
	\| Text Classification \| 94.7% \| 88.2% \| +6.5% \|
	\| Named Entity Recognition \| 92.3% \| 85.9% \| +6.4% \|
	\| Sentiment Analysis \| 89.8% \| 81.3% \| +8.5% \|
	\| Question Answering \| 87.6% \| 79.1% \| +8.5% \|
	\| Text Generation (BLEU) \| 0.731 \| 0.658 \| +11.1% \|
	\| Speech Recognition (WER) \| 6.4% \| 11.7% \| -5.3% (better) \|
	\| Text-to-Speech (MOS) \| 4.52/5 \| 3.87/5 \| +16.8% \|

	Benchmarks conducted using standard Bangla test sets and industry metrics. Full methodology available in our [technical paper](https://shobdhonic.com/research/benchmarks).

	---

	## 📊 Enterprise Solutions
	<div align="center">
	<a href="https://shobdhonic.com/enterprise">
	<img src="https://img.shields.io/badge/Shobdhonic_Enterprise-Get_Custom_Solutions-f42a41?style=for-the-badge&logo=gitlab">
	</a>
	</div>

	### Banking & Finance
	- Fraud detection in Bangla SMS/call transcripts
	- Customer support automation
	- Financial document processing
	- Transaction pattern analysis
	- Risk assessment NLP

	### Media & Publishing
	- Auto-summarize news articles from Prothom Alo/Ittefaq
	- Content recommendation engines
	- Automated content tagging
	- Engagement prediction
	- Toxic comment filtering

	### Education
	- Essay grading and feedback
	- Personalized learning content
	- Question generation from textbooks
	- Academic plagiarism detection
	- Educational chatbots in Bangla

	### Government & NGOs
	- Citizen feedback analysis
	- Service request categorization
	- Policy document processing
	- Public sentiment monitoring
	- Disinformation detection

	---

	## 💻 API Integration

	### REST API Example
	```javascript
	// Using fetch in JavaScript
	const fetchMeme = async () => {
	const response = await fetch('https://api.shobdhonic.com/v1/create-meme', {
	method: 'POST',
	headers: {
	'Content-Type': 'application/json',
	'Authorization': 'Bearer YOUR_API_KEY'
	},
	body: JSON.stringify({
	text: 'পরীক্ষার রেজাল্ট দেখার পর আমি',
	template: 'sad_pepe',
	format: 'jpg'
	})
	});

	const data = await response.json();
	return data.meme_url;
	};

	// Call the function
	fetchMeme().then(url => {
	document.getElementById('meme-image').src = url;
	});
	```

	### Python SDK Example
	```python
	from shobdhonic import ShobdhonicClient
	import asyncio

	async def main():
	# Initialize client
	client = ShobdhonicClient(api_key="YOUR_API_KEY")

	# Use the sentiment analysis API
	result = await client.analyze_sentiment(
	text="এই সিনেমাটা দেখে আমি খুবই মুগ্ধ হয়েছি।",
	detailed=True
	)

	print(f"Overall sentiment: {result.sentiment}")
	print(f"Confidence score: {result.confidence:.2f}")
	print(f"Emotional breakdown: {result.emotions}")

	# Use the translation API
	translation = await client.translate(
	text="আমি বাংলায় কথা বলতে পারি।",
	target_language="en"
	)

	print(f"Translation: {translation.text}")
	print(f"Source language detected: {translation.source_language}")

	# Run the async function
	asyncio.run(main())
	```

	### Webhook Integration
	```python
	from flask import Flask, request, jsonify
	import hmac
	import hashlib

	app = Flask(__name__)

	@app.route('/webhook/shobdhonic', methods=['POST'])
	def shobdhonic_webhook():
	# Verify the webhook signature
	signature = request.headers.get('X-Shobdhonic-Signature')
	secret = 'your_webhook_secret'

	computed_signature = hmac.new(
	secret.encode('utf-8'),
	request.data,
	hashlib.sha256
	).hexdigest()

	if not hmac.compare_digest(signature, computed_signature):
	return jsonify({'error': 'Invalid signature'}), 401

	# Process the webhook data
	data = request.json
	event_type = data.get('event_type')

	if event_type == 'sentiment_alert':
	handle_sentiment_alert(data)
	elif event_type == 'content_moderation':
	handle_content_moderation(data)
	elif event_type == 'trend_detected':
	handle_trend_detection(data)

	return jsonify({'status': 'success'}), 200

	def handle_sentiment_alert(data):
	# Process sentiment alerts
	pass

	def handle_content_moderation(data):
	# Process content moderation events
	pass

	def handle_trend_detection(data):
	# Process trend detection events
	pass

	if __name__ == '__main__':
	app.run(debug=True, port=5000)
	```

	---

	## 🧩 Project Structure
	```
	shobdhonic/
	├── api/ # API endpoints
	├── cli/ # Command-line tools
	├── core/ # Core functionality
	│ ├── models/ # ML models
	│ ├── processors/ # Text processors
	│ ├── tokenizers/ # Bangla tokenizers
	│ └── vectors/ # Word embeddings
	├── data/ # Data handling
	│ ├── corpus/ # Text corpora
	│ ├── loaders/ # Data loaders
	│ └── scrapers/ # Web scrapers
	├── media/ # Media generation
	│ ├── audio/ # Audio processing
	│ ├── images/ # Image generation
	│ └── video/ # Video processing
	├── security/ # Security tools
	├── services/ # External services
	├── ui/ # User interfaces
	│ ├── web/ # Web interface
	│ ├── mobile/ # Mobile interface
	│ └── widgets/ # Embeddable widgets
	├── utils/ # Utility functions
	└── tests/ # Test suite
	```

	---

	## 🛠️ Development Workflow

	### Setting Up Development Environment
	```bash
	# Clone the development repository
	git clone https://github.com/Shobdhonic/shobdhonic-dev.git
	cd shobdhonic-dev

	# Create development environment
	python -m venv dev-env
	source dev-env/bin/activate

	# Install development dependencies
	pip install -r requirements-dev.txt

	# Set up pre-commit hooks
	pre-commit install
	```

	### Running Tests
	```bash
	# Run all tests
	pytest

	# Run specific test category
	pytest tests/test_tokenizers.py

	# Run with coverage report
	pytest --cov=shobdhonic --cov-report=html
	```

	### Building Documentation
	```bash
	# Generate API documentation
	cd docs
	make html

	# View documentation
	python -m http.server -d _build/html
	```

	### CI/CD Pipeline
	Our continuous integration and deployment pipeline automatically:
	1. Runs tests on all pull requests
	2. Performs code quality checks
	3. Builds and publishes packages on releases
	4. Deploys to staging/production environments
	5. Updates documentation site

	---

	## 🤝 Contribute to Bangla AI
	We welcome contributions from the community! Here's how to get started:

	1. Fork the Repository: [GitHub/Shobdhonic](https://github.com/Shobdhonic)
	2. Pick an Issue: Look for issues labeled `good-first-issue`, `help-wanted`, or `Gen-Z feature`
	3. Set Up Your Environment: Follow the development setup instructions above
	4. Make Your Changes: Write code and tests for your feature or fix
	5. Submit a Pull Request: Follow our [Contribution Guidelines](CONTRIBUTING.md)

	### Areas We Need Help With
	- 🧠 Model Training: Fine-tuning transformers on Bangla data
	- 🎮 Gen-Z Features: Cultural memes, slang translators, social integrations
	- 📱 Mobile Development: React Native components for our SDK
	- 🔊 Voice Data: Collection and processing of regional dialects
	- 📚 Documentation: Tutorials, examples, and API documentation

	### Contributor Code of Conduct
	All contributors are expected to adhere to our [Code of Conduct](CODE_OF_CONDUCT.md) which promotes a welcoming, inclusive, and harassment-free experience for everyone.

	---

	## 📒 Documentation

	### API Reference
	Complete API documentation is available at [docs.shobdhonic.com](https://docs.shobdhonic.com)

	### Tutorials
	Step-by-step tutorials for common tasks:
	- [Getting Started with Shôbdhonic](https://docs.shobdhonic.com/tutorials/getting-started)
	- [Building a Bangla Chatbot](https://docs.shobdhonic.com/tutorials/chatbot)
	- [Voice Cloning Basics](https://docs.shobdhonic.com/tutorials/voice-cloning)
	- [Meme Generation](https://docs.shobdhonic.com/tutorials/meme-gen)
	- [Enterprise Document Processing](https://docs.shobdhonic.com/tutorials/document-processing)

	### Examples
	Explore our [examples directory](https://github.com/Shobdhonic/examples) for complete code samples:
	- Basic NLP tasks (tokenization, classification, etc.)
	- Voice synthesis and analysis
	- Media generation workflows
	- Enterprise integration patterns
	- Web and mobile application samples

	---

	## 📜 License & Ethics
	```text
	MIT License \| © 2024 Shôbdhonic

	Bangla Data Ethics Pledge:
	- No misuse of dialects/regional languages
	- Cite sources like Ittefaq/Prothom Alo
	- Free access for academic research and non-profits/NGOs
	- Respecting privacy and data sovereignty
	- Preserving Bangla linguistic diversity
	```

	### Ethical AI Commitment
	At Shôbdhonic, we commit to:
	- Transparency in our AI systems
	- Fairness and bias mitigation
	- Protection of user privacy
	- Responsible data collection practices
	- Supporting cultural preservation
	- Making advanced Bangla NLP accessible to all

	Our complete AI Ethics Policy is available [here](https://shobdhonic.com/ethics).

	---

	## 🧪 Research
	Our team publishes open research on Bangla NLP:

	- [BanglaTransformers: Pre-training Transformers for Bengali NLP](https://arxiv.org/abs/xxxx.xxxxx)
	- [Dialect-Aware Speech Synthesis for Low-Resource Languages](https://arxiv.org/abs/xxxx.xxxxx)
	- [BanglaEval: Benchmarking NLP Systems for Bengali](https://arxiv.org/abs/xxxx.xxxxx)

	Interested in research collaboration? Contact us at [email protected]

	---

	## 🌐 Connect
	<div align="center">

	[![Hugging Face](https://img.shields.io/badge/Models-Hugging_Face-ffcc00?style=for-the-badge&logo=huggingface)](https://huggingface.co/Shobdhonic)
	[![YouTube](https://img.shields.io/badge/Tutorials-YouTube-FF0000?style=for-the-badge&logo=youtube)](https://youtube.com/Shobdhonic)
	[![LinkedIn](https://img.shields.io/badge/Jobs-LinkedIn-0A66C2?style=for-the-badge&logo=linkedin)](https://linkedin.com/company/Shobdhonic)
	[![Medium](https://img.shields.io/badge/Blog-Medium-000000?style=for-the-badge&logo=medium)](https://medium.com/Shobdhonic)
	[![Discord](https://img.shields.io/badge/Community-Discord-5865F2?style=for-the-badge&logo=discord)](https://discord.gg/shobdhonic)

	</div>

	---

	<div align="center">

	মহাযুদ্ধ বাংলা ভাষার, আমরা প্রস্তুত!
	Powered by রক্তে বাংলা, প্রযুক্তিতে Shôbdhonic

	</div>