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The Practical Use of the A* Algorithm for Exact Multiple Sequence Alignment
 Journal of Computational Biology
, 1997
"... Multiple alignment is an important problem in computational biology. It is well known that it can be solved exactly by a dynamic programming algorithm which in turn can be interpreted as a shortest path computation in a directed acyclic graph. The A algorithm (or goal directed unidirectional search ..."
Abstract

Cited by 22 (4 self)
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Multiple alignment is an important problem in computational biology. It is well known that it can be solved exactly by a dynamic programming algorithm which in turn can be interpreted as a shortest path computation in a directed acyclic graph. The A algorithm (or goal directed unidirectional search) is a technique that speeds up the computation of a shortest path by transforming the edge lengths without losing the optimality of the shortest path. We implemented the A algorithm in a computer program similar to MSA [GKS95] and FMA [SI97b]. We incorporated in this program new bounding strategies for both, lower and upper bounds and show that the A algorithm, together with our improvements, can speed up computations considerably. Additionally we show that the A algorithm together with a standard bounding technique is superior to the well known CarilloLipman bounding since it excludes more nodes from consideration. 1 Introduction One of the most prominent problems in computational mo...
Text Alignment for RealTime Crowd Captioning
"... The primary way of providing realtime captioning for deaf and hard of hearing people is to employ expensive professional stenographers who can type as fast as natural speaking rates. Recent work has shown that a feasible alternative is to combine the partial captions of ordinary typists, each of wh ..."
Abstract

Cited by 3 (3 self)
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The primary way of providing realtime captioning for deaf and hard of hearing people is to employ expensive professional stenographers who can type as fast as natural speaking rates. Recent work has shown that a feasible alternative is to combine the partial captions of ordinary typists, each of whom types part of what they hear. In this paper, we describe an improved method for combining partial captions into a final output based on weighted A ∗ search and multiple sequence alignment (MSA). In contrast to prior work, our method allows the tradeoff between accuracy and speed to be tuned, and provides formal error bounds. Our method outperforms the current stateoftheart on Word Error Rate (WER) (29.6%), BLEU Score (41.4%), and Fmeasure (36.9%). The end goal is for these captions to be used by people, and so we also compare how these metrics correlate with the judgments of 50 study participants, which may assist others looking to make further progress on this problem. 1