This paper addresses the problem of on-line, writer-independent, unconstrained handwriting recognition. Based on Hidden Markov Models (HMM), which are successfully employed in speech recognition tasks, we focus on representations which address scalability, recognition performance and compactness. `Delayed' features are introduced which i n tegrate more global, handwriting specic knowledge into ...