Multilingual machine printed OCR
Hidden Markov models
Named entity extraction from noisy input: speech and OCR
ANLC '00 Proceedings of the sixth conference on Applied natural language processing
Performance Improvements to the BBN Byblos OCR System
ICDAR '05 Proceedings of the Eighth International Conference on Document Analysis and Recognition
Character Duration Modeling for Speed Improvements in the BBN Byblos OCR System
ICDAR '05 Proceedings of the Eighth International Conference on Document Analysis and Recognition
Adapting the Tesseract open source OCR engine for multilingual OCR
Proceedings of the International Workshop on Multilingual OCR
Recent progress on the OCRopus OCR system
Proceedings of the International Workshop on Multilingual OCR
Efficient search in document image collections
ACCV'07 Proceedings of the 8th Asian conference on Computer vision - Volume Part I
SACH'06 Proceedings of the 2006 conference on Arabic and Chinese handwriting recognition
The BBN document analysis service: a platform for multilingual document translation
DAS '10 Proceedings of the 9th IAPR International Workshop on Document Analysis Systems
| Hi-index | 0.00 |
In this paper, we present some recent advances in the BBN BYBLOS OCR system. This OCR system can be used to recognize Arabic, Chinese, and English with high accuracy. A major change in the system is the use of continuous-density HMMs, which allow us to take advantage of large amount of training data and to use unsupervised adaptation methods to improve accuracy in many cases, e.g. on degraded data. Another advance is the substantial increase in recognition speed. With this increased speed, the system is fast enough for practical use on Arabic and English data. The extension of the system to Chinese further demonstrated the language independence of this system and showed that this system can be used on languages with large character sets and complicated character structures. The Chinese OCR system yielded high accuracy on newspaper data.