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Large-Vocabulary Speech Recognition Algorithms

by Ibm T. J. Watson
"... By making the advances necessary to implement next-generation speech recognition applications, researchers could develop systems within a decade that match human performance levels. Providing the computer with a natural interface, including the ability to understand human speech, has been a research ..."
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research goal for almost 40 years. Speech recognition research started with an attempt to decode isolated words from a small vocabulary. As time progressed, the research community began working on large-vocabulary and continuousspeech tasks. Practical versions of such systems have become moderately usable

A maximum likelihood approach to continuous speech recognition

by Lalit R. Bahl, Frederick Jelinek, Robert, L. Mercer - IEEE Trans. Pattern Anal. Machine Intell , 1983
"... Abstract-Speech recognition is formulated as a problem of maximum likelihood decoding. This formulation requires statistical models of the speech production process. In this paper, we describe a number of sta-tistical models for use in speech recognition. We give special attention to determining the ..."
Abstract - Cited by 472 (9 self) - Add to MetaCart
Abstract-Speech recognition is formulated as a problem of maximum likelihood decoding. This formulation requires statistical models of the speech production process. In this paper, we describe a number of sta-tistical models for use in speech recognition. We give special attention to determining

Maximum Likelihood Linear Transformations for HMM-Based Speech Recognition

by M.J.F. Gales - Computer Speech and Language , 1998
"... This paper examines the application of linear transformations for speaker and environmental adaptation in an HMM-based speech recognition system. In particular, transformations that are trained in a maximum likelihood sense on adaptation data are investigated. Other than in the form of a simple bias ..."
Abstract - Cited by 538 (65 self) - Add to MetaCart
-space transforms on a large vocabulary speech recognition task using incremental adaptation is investigated. In addition, initial experiments using the constrained model-space transform for speaker adaptive training are detailed. 1 The author is now at the IBM T.J. Watson Research Center, Yorktown Heights, NY

A review of large-vocabulary . . .

by Steve Young , 1996
"... Considerable progress has been made in speech-recognition technology over the last few years and nowhere has this progress been more evident than in the area of large-vocabulary recognition (LVR). Current laboratory systems are capable of transcribing continuous speech from any speaker with average ..."
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Considerable progress has been made in speech-recognition technology over the last few years and nowhere has this progress been more evident than in the area of large-vocabulary recognition (LVR). Current laboratory systems are capable of transcribing continuous speech from any speaker with average

Comparison of parametric representations for monosyllabic word recognition in continuously spoken sentences

by Steven B. Davis, Paul Mermelstein - ACOUSTICS, SPEECH AND SIGNAL PROCESSING, IEEE TRANSACTIONS ON , 1980
"... Several parametric representations of the acoustic signal were compared as to word recognition performance in a syllable-oriented continuous speech recognition system. The vocabulary in-cluded many phonetically similar monosyllabic words, therefore the emphasis was on ability to retain phonetically ..."
Abstract - Cited by 1089 (2 self) - Add to MetaCart
Several parametric representations of the acoustic signal were compared as to word recognition performance in a syllable-oriented continuous speech recognition system. The vocabulary in-cluded many phonetically similar monosyllabic words, therefore the emphasis was on ability to retain

Face Recognition: A Literature Survey

by W. Zhao, R. Chellappa, P. J. Phillips, A. Rosenfeld , 2000
"... ... This paper provides an up-to-date critical survey of still- and video-based face recognition research. There are two underlying motivations for us to write this survey paper: the first is to provide an up-to-date review of the existing literature, and the second is to offer some insights into ..."
Abstract - Cited by 1363 (21 self) - Add to MetaCart
into the studies of machine recognition of faces. To provide a comprehensive survey, we not only categorize existing recognition techniques but also present detailed descriptions of representative methods within each category. In addition,

An introduction to variable and feature selection

by Isabelle Guyon - Journal of Machine Learning Research , 2003
"... Variable and feature selection have become the focus of much research in areas of application for which datasets with tens or hundreds of thousands of variables are available. ..."
Abstract - Cited by 1283 (16 self) - Add to MetaCart
Variable and feature selection have become the focus of much research in areas of application for which datasets with tens or hundreds of thousands of variables are available.

Wrappers for Feature Subset Selection

by Ron Kohavi, George H. John - AIJ SPECIAL ISSUE ON RELEVANCE , 1997
"... In the feature subset selection problem, a learning algorithm is faced with the problem of selecting a relevant subset of features upon which to focus its attention, while ignoring the rest. To achieve the best possible performance with a particular learning algorithm on a particular training set, a ..."
Abstract - Cited by 1522 (3 self) - Add to MetaCart
In the feature subset selection problem, a learning algorithm is faced with the problem of selecting a relevant subset of features upon which to focus its attention, while ignoring the rest. To achieve the best possible performance with a particular learning algorithm on a particular training set

Local features and kernels for classification of texture and object categories: a comprehensive study

by J. Zhang, S. Lazebnik, C. Schmid - International Journal of Computer Vision , 2007
"... Recently, methods based on local image features have shown promise for texture and object recognition tasks. This paper presents a large-scale evaluation of an approach that represents images as distributions (signatures or histograms) of features extracted from a sparse set of keypoint locations an ..."
Abstract - Cited by 644 (35 self) - Add to MetaCart
Recently, methods based on local image features have shown promise for texture and object recognition tasks. This paper presents a large-scale evaluation of an approach that represents images as distributions (signatures or histograms) of features extracted from a sparse set of keypoint locations

Transformation-Based Error-Driven Learning and Natural Language Processing: A Case Study in Part-of-Speech Tagging

by Eric Brill - Computational Linguistics , 1995
"... this paper, we will describe a simple rule-based approach to automated learning of linguistic knowledge. This approach has been shown for a number of tasks to capture information in a clearer and more direct fashion without a compromise in performance. We present a detailed case study of this learni ..."
Abstract - Cited by 916 (7 self) - Add to MetaCart
of this learning method applied to part of speech tagging
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