Abstract
The method of dynamic time warping is a well-established technique for time alignment and comparison of speech and image patterns. It has found extensive application in speech recognition and related areas of pattern matching. Comparing the handwritten symbol to the set of training symbols (called reference symbols), we can recognize the input handwritten symbol by computing the distances among the input symbol and the reference symbols in the training set. In this paper we propose a VLSI architecture based on the space-time domain expansion which can compute the symbol distance and also give the index pairs which correspond to the warp function. The time complexity is O(max(m, n)) by using m × n processing elements array, where m is the length of the input symbol and n is the length of the reference symbol. With a uniprocessor, the matching process will have the time complexity O(m × n). If there are p reference symbols, using the proposed architecture, the recognition problem can be solved in time O(max(m, n, p)). With a uniprocessor, the time complexity will be O(m × n × p). The algorithm partition problems are discussed. Verification of the proposed VLSI architecture is also given.
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More From: IEEE Transactions on Acoustics, Speech, and Signal Processing
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