paper-voice 0.1.0

Convert academic PDFs to spoken audio, handling math, tables and figures

Paper Voice

Convert academic PDFs to audio with proper mathematical notation handling.

Features

• Math handling: Converts LaTeX expressions to natural speech (e.g., $\alpha^2$ → "alpha squared")
• LLM-powered explanations: Uses GPT-4 to explain complex mathematical expressions clearly
• Figure/table summaries: Extracts and summarizes figure captions and table content
• Multiple TTS options: Offline (pyttsx3) or OpenAI TTS
• Direct LaTeX/Markdown support: Process text with math notation directly
• Web interface: Streamlit app for easy file uploads and processing

Installation

git clone <your-repo-url>
cd paper_voice
pip install -e .

Usage

Web Interface

streamlit run paper_voice/streamlit/app.py

Upload a PDF, LaTeX file, or enter text directly. For best results with mathematical content, provide an OpenAI API key to enable LLM-powered explanations.

Command Line

from paper_voice import pdf_utils, math_to_speech

# Extract text from PDF
pages = pdf_utils.extract_raw_text("paper.pdf")

# Process mathematical expressions
processed = math_to_speech.process_text_with_math(pages[0])
print(processed)

Requirements

• Python 3.9+ (excluding 3.9.7)
• OpenAI API key (optional, for enhanced math explanations)
• ffmpeg (for audio processing)

Applications

There are several Streamlit applications available:

• paper_voice/streamlit/app.py - Basic PDF to audio conversion
• paper_voice/streamlit/app_with_llm.py - Enhanced with LLM math explanations
• paper_voice/streamlit/app_enhanced.py - Full-featured version with LaTeX/Markdown support

Examples

See the demos/ directory for usage examples:

• demos/basic_usage.py - Simple math processing examples
• demos/before_after_comparison.py - Shows improvement from LLM explanations

See the tests/ directory for test cases.