SYSTEM AND METHOD FOR PRUNING A SET OF SYMBOL-BASED SEQUENCES BY RELAXING AN INDEPENDENCE ASSUMPTION OF THE SEQUENCES

A pruning method includes representing a set of sequences in a data structure. Each sequence s includes a first symbol w and a context c of at least one symbol. Some of the sequences are associated with a conditional probability p(w|c), based on observations of cw in training data. For others, p(w|c) is computed as a function of the probability p(w|ĉ) of the respective symbol w in a back-off context ĉ, p(w|ĉ) being based on observations of sequence ĉw in the training data. A scoring function ƒ(cw) value is computed for each sequence in the set, based on p(w|c) for the sequence and a probability distribution p(s) of each symbol in the sequence if it is removed from the set of sequences. Iteratively, one of the represented sequences is selected to be removed, based on the computed scoring function values, and the scoring function values of remaining sequences are updated.