A media monitoring agency must extract Russian, Ukrainian, and Polish text from daily PDF bulletins to feed into sentiment analysis APIs. They require a solution that retains the original Cyrillic without transliteration.
To prepare content for extraction using the multilingual-pdf2text Python library, you need to set up the environment with Tesseract OCR and configure the object for your specific file and language. 1. Environment Preparation The library relies on Tesseract OCR to handle text extraction from various languages. Install the Python package pip install multilingual-pdf2text Install Tesseract : Follow the official Tesseract installation guides for your OS (e.g., apt install tesseract-ocr on Linux/Colab). Add Language Packs multilingual-pdf2text
For scanned PDFs or image-only files, a multilingual OCR engine (like Tesseract 5+ with LSTM models or Google Cloud Document AI) scans the image. It identifies text lines, recognizes script direction, and applies a language-specific neural network. For multilingual documents (e.g., a French research paper with English abstracts), the engine may switch models mid-page. A media monitoring agency must extract Russian, Ukrainian,
