OCR for Indian languages has made significant progress, with many tools now supporting scripts like Devanagari, Bengali, Tamil, and Telugu. Solutions such as Google Tesseract and Microsoft Azure OCR offer robust support for printed text recognition in Indian languages. However, challenges remain in recognizing handwritten text and degraded documents, as the complexity of Indic scripts and lack of high-quality datasets limit accuracy. Ongoing research and the use of deep learning models are improving performance. Initiatives like Google’s Project Sandhan and specialized regional OCR systems are helping bridge the gap. While OCR for Indian languages is not yet perfect, it is steadily improving and becoming more accessible.
What is the Status of OCR in Indian languages?
Keep Reading
How is data integrity ensured in relational databases?
Data integrity in relational databases is ensured through a combination of methods that help maintain the accuracy, cons
How are Sentence Transformers used in semantic search engines or information retrieval systems?
Sentence Transformers are used in semantic search engines and information retrieval systems to convert text into numeric
How do speech recognition systems adapt to user-specific speech patterns?
Speech recognition systems adapt to user-specific speech patterns through a combination of acoustic modeling, language m