Combinatorial Optimization Approach for Arabic Word Recognition

In this work, we propose an approach based on combinatorial optimization technique for Arabic word recognition that has been a challenge because of the significant topological variability and the complex inflectional nature of Arabic language. We handle a wide vocabulary of Arabic decomposable words, which we have decided to structure as a molecular cloud. This design rhymes well with the Arabic linguistic philosophy of constructing words around roots. Each sub-cloud includes neighboring words that derive from the same root and follow different forms of derivation, flexion, and agglutination (proclitic and enclitic). Thereby, we propose -as a recognition approach- to use on this enormous cloud, the technique of simulated annealing. Its algorithm is based on an elastic comparison between sequences of structural primitives. Preliminary experiments are carried on Arabic word corpus including samples from APTI database and first results are promising.