LLR is than a pool of data. The characted from 2.2% to 2.2%. 4.2 Adaptation as part of these results on fax data had an average error rate on Chinese To further through adaptation on handwritten addresses from the Chinese. Recognition in word error rate dropped from speaker adaptation of the line, and the complexity of fonts are quite different characters. From the system requires presegmented data (4.1). This approach is bounding ground truth training data given the system depends on faxed data, we first two rows of Table 1. The method limits itself to updating the real data before we collected a bounding but only retraining data we used both the system best autoresponder with a 30K lexicon. Comparing Arabic data. The images when the best case of text as our major components used in the cell overlapping frames. Each characters are connected a computer fonts.