Journal ArticleDOI
The use of a one-stage dynamic programming algorithm for connected word recognition
TLDR
The algorithm to be developed is essentially identical to one presented by Vintsyuk and later by Bridle and Brown, but the notation and the presentation have been clarified and the computational expenditure per word is independent of the number of words in the input string.Abstract:
This paper is of tutorial nature and describes a one-stage dynamic programming algorithm for file problem of connected word recognition. The algorithm to be developed is essentially identical to one presented by Vintsyuk [1] and later by Bridle and Brown [2] ; but the notation and the presentation have been clarified. The derivation used for optimally time synchronizing a test pattern, consisting of a sequence of connected words, is straightforward and simple in comparison with other approaches decomposing the pattern matching problem into several levels. The approach presented relies basically on parameterizing the time warping path by a single index and on exploiting certain path constraints both in the word interior and at the word boundaries. The resulting algorithm turns out to be significantly more efficient than those proposed by Sakoe [3] as well as Myers and Rabiner [4], while providing the same accuracy in estimating the best possible matching string. Its most important feature is that the computational expenditure per word is independent of the number of words in the input string. Thus, it is well suited for recognizing comparatively long word sequences and for real-time operation. Furthermore, there is no need to specify the maximum number of words in the input string. The practical implementation of the algorithm is discussed; it requires no heuristic rules and no overhead. The algorithm can be modified to deal with syntactic constraints in terms of a finite state syntax.read more
Citations
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Connectionist Speech Recognition: A Hybrid Approach
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TL;DR: Connectionist Speech Recognition: A Hybrid Approach describes the theory and implementation of a method to incorporate neural network approaches into state-of-the-art continuous speech recognition systems based on Hidden Markov Models (HMMs) to improve their performance.
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Applications of stochastic context-free grammars using the Inside-Outside algorithm
K. Lari,Steve Young +1 more
TL;DR: Two applications in speech recognition of the use of stochastic context-free grammars trained automatically via the Inside-Outside Algorithm, used to model VQ encoded speech for isolated word recognition and compared directly to HMMs used for the same task are described.
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Survey of the State of the Art in Human Language Technology
TL;DR: In this article, the authors present a glossary for language analysis and understanding in the context of spoken language input and output technologies, and evaluate their work with a set of annotated corpora.
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Synchronization of batch trajectories using dynamic time warping
TL;DR: In this article, the application of dynamic time warping (DTW) to the analysis and monitoring of batch processes is presented, which has the ability to synchronize two trajectories by appropriately translating, expanding, and contracting localized segments within both trajectories to achieve a minimum distance between the trajectories.
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Links between Markov models and multilayer perceptrons
Hervé Bourlard,C. Wellekens +1 more
TL;DR: It is shown theoretically and experimentally that the outputs of the MLP approximate the probability distribution over output classes conditioned on the input, i.e. the maximum a posteriori probabilities.
References
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Book
Dynamic Programming
TL;DR: The more the authors study the information processing aspects of the mind, the more perplexed and impressed they become, and it will be a very long time before they understand these processes sufficiently to reproduce them.
Journal ArticleDOI
Dynamic programming algorithm optimization for spoken word recognition
TL;DR: This paper reports on an optimum dynamic progxamming (DP) based time-normalization algorithm for spoken word recognition, in which the warping function slope is restricted so as to improve discrimination between words in different categories.
Journal ArticleDOI
Minimum prediction residual principle applied to speech recognition
TL;DR: A computer system is described in which isolated words, spoken by a designated talker, are recognized through calculation of a minimum prediction residual through optimally registering the reference LPC onto the input autocorrelation coefficients using the dynamic programming algorithm.
Journal ArticleDOI
The DRAGON system--An overview
TL;DR: This paper briefly describes the major features of the DRAGON speech understanding system, which makes systematic use of a general abstract model to represent each of the knowledge sources necessary for automatic recognition of continuous speech.
Book
The HARPY speech recognition system
TL;DR: The HARPY system is the result of an attempt to understand the relative importance of various design choices of two earlier speech recognition systems developed at Carnegie-Mellon University, in which knowledge is represented as a finite state transition network but without the a-priori transition probabilities.
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