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An introduction to software architecture
 Advances in Software Engineering and Knowledge Engineering
, 1993
"... ..."
Regular Model Checking
, 2000
"... . We present regular model checking, a framework for algorithmic verification of infinitestate systems with, e.g., queues, stacks, integers, or a parameterized linear topology. States are represented by strings over a finite alphabet and the transition relation by a regular lengthpreserving re ..."
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Cited by 165 (25 self)
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. We present regular model checking, a framework for algorithmic verification of infinitestate systems with, e.g., queues, stacks, integers, or a parameterized linear topology. States are represented by strings over a finite alphabet and the transition relation by a regular length
The reactive engine for modular transducers
 Algebra, Meaning and Computation, Essays Dedicated to Joseph A. Goguen on the Occasion of His 65th Birthday
, 2005
"... Abstract. This paper explains the design of the second release of the Zen toolkit [5–7]. It presents a notion of reactive engine which simulates finitestate machines represented as shared aums [8]. We show that it yields a modular interpreter for finite state machines described as local transducers ..."
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Cited by 10 (9 self)
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transducers. For instance, in the manner of Berry and Sethi, we define a compiler of regular expressions into a scheduler for the reactive engine, chaining through aums labeled with phases — associated with the letters of the regular expression. This gives a modular composition scheme for general finite
Transducers with origin information
 In ICALP
, 2014
"... Call a stringtostring transducer regular if it can be realised by one of the following equivalent models: mso transductions, twoway deterministic automata with output, and streaming transducers with registers. This paper proposes to treat origin information as part of the semantics of a regular ..."
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Cited by 6 (0 self)
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Call a stringtostring transducer regular if it can be realised by one of the following equivalent models: mso transductions, twoway deterministic automata with output, and streaming transducers with registers. This paper proposes to treat origin information as part of the semantics of a regular
Parameter Estimation for Probabilistic FiniteState Transducers
 Proc. of the Annual Meeting of the Association for Computational Linguistics
, 2002
"... Weighted finitestate transducers suffer from the lack of a training algorithm. Training is even harder for transducers that have been assembled via finitestate operations such as composition, minimization, union, concatenation, and closure, as this yields tricky parameter tying. We formulate a &qu ..."
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Cited by 57 (4 self)
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Weighted finitestate transducers suffer from the lack of a training algorithm. Training is even harder for transducers that have been assembled via finitestate operations such as composition, minimization, union, concatenation, and closure, as this yields tricky parameter tying. We formulate a
Signal modeling techniques in speech recognition
 PROCEEDINGS OF THE IEEE
, 1993
"... We have seen three important trends develop in the last five years in speech recognition. First, heterogeneous parameter sets that mix absolute spectral information with dynamic, or timederivative, spectral information, have become common. Second, similariry transform techniques, often used to norm ..."
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Cited by 180 (5 self)
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We have seen three important trends develop in the last five years in speech recognition. First, heterogeneous parameter sets that mix absolute spectral information with dynamic, or timederivative, spectral information, have become common. Second, similariry transform techniques, often used to normalize and decorrelate parameters in some computationally inexpensive way, have become popular. Third, the signal parameter estimation problem has merged with the speech recognition process so that more sophisticated statistical models of the signal’s spectrum can be estimated in a closedloop manner. In this paper, we review the signal processing components of these algorithms. These algorithms are presented as part of a unified view of the signal parameterization problem in which there are three major tasks: measurement, transformation, and statistical modeling. This paper is by no means a comprehensive survey of all possible techniques of signal modeling in speech recognition. There are far too many algorithms in use today to make an exhaustive survey feasible (and cohesive). Instead, this paper is meant to serve as a tutorial on signal processing in stateoftheart speech recognition systems and to review those techniques most commonly used. In keeping with this goal, a complete mathematical description of each algorithm has been included in the paper.
A Decision Procedure for Subset Constraints over Regular Languages
 PLDI'09
, 2009
"... Reasoning about string variables, in particular program inputs, is an important aspect of many program analyses and testing frameworks. Program inputs invariably arrive as strings, and are often manipulated using highlevel string operations such as equality checks, regular expression matching, and ..."
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Cited by 49 (12 self)
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Reasoning about string variables, in particular program inputs, is an important aspect of many program analyses and testing frameworks. Program inputs invariably arrive as strings, and are often manipulated using highlevel string operations such as equality checks, regular expression matching
Approximate string matching
 ACM Computing Surveys
, 1980
"... Approximate matching of strings is reviewed with the aim of surveying techniques suitable for finding an item in a database when there may be a spelling mistake or other error in the keyword. The methods found are classified as either equivalence or similarity problems. Equivalence problems are seen ..."
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Cited by 158 (0 self)
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Approximate matching of strings is reviewed with the aim of surveying techniques suitable for finding an item in a database when there may be a spelling mistake or other error in the keyword. The methods found are classified as either equivalence or similarity problems. Equivalence problems are seen to be readily solved using canonical forms. For sinuiarity problems difference measures are surveyed, with a full description of the wellestablmhed dynamic programming method relating this to the approach using probabilities and likelihoods. Searches for approximate matches in large sets using a difference function are seen to be an open problem still, though several promising ideas have been suggested. Approximate matching (error correction) during parsing is briefly reviewed.
Results 1  10
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