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I have a batch of PDFs made up entirely of scanned images. The scans are of medium quality, so the text is readable but not crystal-clear; careful OCR work and manual proofreading will be required. All I need back is clean, plain UTF-8 text—no layout reconstruction, styling, or headers necessary. Speed is important: this project is time-sensitive and I’m ready to start as soon as I select the freelancer. Tools such as Tesseract, ABBYY FineReader, or Adobe Acrobat’s OCR module are fine, provided the final output meets the accuracy standard below. Deliverables • A separate .txt file for each source PDF, named to match the original file • Spelling and obvious recognition errors corrected • Any unreadable characters clearly flagged with “[unreadable]&rd...

I have a collection of scanned PDFs that I need turned into clean, machine-readable text so I can pull specific data points out later on. The files are almost entirely straightforward paragraphs—no tables, forms, or complex layouts—so the goal is simple: run accurate OCR, proof the output, and supply me with text files that mirror the original wording and structure line for line. You’re free to use whichever OCR workflow you trust most (Tesseract, ABBYY, Adobe, or a custom Python script), as long as the final text is: • Fully searchable and copy-pastable • Formatted to match the original paragraphs • 99 %+ accurate when compared against the source pages Please return one UTF-8 plain-text file per PDF along with a quick note on the toolchain you used,...

I have 50 high-resolution JPG/PNG pages that record Viennese street name changes—they map the historic to current ones. I need these pages converted into editable text with publication-grade accuracy. Because the files are already digital, no physical scanning is required; the job is all about precise OCR and meticulous proofreading. You may use any robust engine you prefer—ABBYY FineReader, a finely-tuned Tesseract model, or similar—but the end result must be spotless German text, including every umlaut and ß exactly as printed. The layout is simple: two columns per entry, so please preserve that structure. Add any additional information and problems you encounter. Deliverables • A UTF-8 Excel or CSV file with columns: old_name | new_name | page_number &b...

I have 50 high-resolution JPG/PNG pages that record Viennese street name changes—they map the historic to current ones. I need these pages converted into editable text with publication-grade accuracy. Because the files are already digital, no physical scanning is required; the job is all about precise OCR and meticulous proofreading. You may use any robust engine you prefer—ABBYY FineReader, a finely-tuned Tesseract model, or similar—but the end result must be spotless German text, including every umlaut and ß exactly as printed. The layout is simple: two columns per entry, so please preserve that structure. Add any additional information and problems you encounter. Deliverables • A UTF-8 Excel or CSV file with columns: old_name | new_name | page_number &b...

We are hiring remote contributors to create photo-based language data using everyday materials found around you. This project focuses on collecting natural, real-life text captured through a phone camera. What You’ll Do - Photograph common objects that contain written text (printed or handwritten). - Provide three unique shots per item, changing position, distance, or lighting. - Ensure content is original and varied. - Most of the visible text (minimum 75%) must be in your local language. Eligibility - Fluent in the target language (native or near-native). - Physically located in a country where the language is used. - Own a smartphone capable of taking clear photos. How It Works - Upload images through a Google Form. - Submissions are reviewed individually. - Only valid, clear, ...