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48,198
A Study of the Automatic Speech Recognition Process and Speaker Adaptation
, 2000
"... University ofWaterloo ..."
A maximum likelihood approach to continuous speech recognition
- 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
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Cited by 477 (9 self)
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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
Coupled hidden Markov models for complex action recognition
, 1996
"... We present algorithms for coupling and training hidden Markov models (HMMs) to model interacting processes, and demonstrate their superiority to conventional HMMs in a vision task classifying two-handed actions. HMMs are perhaps the most successful framework in perceptual computing for modeling and ..."
Abstract
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Cited by 501 (22 self)
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and an extremely limited state memory. The single-process model is often inappropriate for vision (and speech) applications, resulting in low ceilings on model performance. Coupled HMMs provide an efficient way to resolve many of these problems, and offer superior training speeds, model likelihoods, and robustness
Maximum Likelihood Linear Transformations for HMM-Based Speech Recognition
- 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
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Cited by 570 (68 self)
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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
A tutorial on hidden Markov models and selected applications in speech recognition
- PROCEEDINGS OF THE IEEE
, 1989
"... Although initially introduced and studied in the late 1960s and early 1970s, statistical methods of Markov source or hidden Markov modeling have become increasingly popular in the last several years. There are two strong reasons why this has occurred. First the models are very rich in mathematical s ..."
Abstract
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Cited by 5892 (1 self)
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of statistical modeling and show how they have been applied to selected problems in machine recognition of speech.
The Aurora Experimental Framework for the Performance Evaluation of Speech Recognition Systems under Noisy Conditions
- in ISCA ITRW ASR2000
, 2000
"... This paper describes a database designed to evaluate the performance of speech recognition algorithms in noisy conditions. The database may either be used to measure frontend feature extraction algorithms, using a defined HMM recognition back-end, or complete recognition systems. The source speech f ..."
Abstract
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Cited by 534 (6 self)
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This paper describes a database designed to evaluate the performance of speech recognition algorithms in noisy conditions. The database may either be used to measure frontend feature extraction algorithms, using a defined HMM recognition back-end, or complete recognition systems. The source speech
Hierarchical Models of Object Recognition in Cortex
, 1999
"... The classical model of visual processing in cortex is a hierarchy of increasingly sophisticated representations, extending in a natural way the model of simple to complex cells of Hubel and Wiesel. Somewhat surprisingly, little quantitative modeling has been done in the last 15 years to explore th ..."
Abstract
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Cited by 836 (84 self)
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the biological feasibility of this class of models to explain higher level visual processing, such as object recognition. We describe a new hierarchical model that accounts well for this complex visual task, is consistent with several recent physiological experiments in inferotemporal cortex and makes testable
A theory of lexical access in speech production
- Behavioral and Brain Research
, 1999
"... The generation of words in speech involves a number of processing stages. There is, first, a stage of conceptual preparation; this is followed by stages of lexical selection, phonological encoding, phonetic encoding and articulation. In addition, the speaker monitors the output and, if necessary, se ..."
Abstract
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Cited by 744 (59 self)
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The generation of words in speech involves a number of processing stages. There is, first, a stage of conceptual preparation; this is followed by stages of lexical selection, phonological encoding, phonetic encoding and articulation. In addition, the speaker monitors the output and, if necessary
A Simple Rule-Based Part of Speech Tagger
, 1992
"... Automatic part of speech tagging is an area of natural language processing where statistical techniques have been more successful than rule- based methods. In this paper, we present a sim- ple rule-based part of speech tagger which automatically acquires its rules and tags with accuracy coinparable ..."
Abstract
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Cited by 596 (9 self)
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Automatic part of speech tagging is an area of natural language processing where statistical techniques have been more successful than rule- based methods. In this paper, we present a sim- ple rule-based part of speech tagger which automatically acquires its rules and tags with accuracy coinparable
Transformation-Based Error-Driven Learning and Natural Language Processing: A Case Study in Part-of-Speech Tagging
- 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
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Cited by 924 (8 self)
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of this learning method applied to part of speech tagging
Results 1 - 10
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48,198
