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Results 1 - 10
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836
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
SRILM -- An extensible language modeling toolkit
- IN PROCEEDINGS OF THE 7TH INTERNATIONAL CONFERENCE ON SPOKEN LANGUAGE PROCESSING (ICSLP 2002
, 2002
"... SRILM is a collection of C++ libraries, executable programs, and helper scripts designed to allow both production of and experimentation with statistical language models for speech recognition and other applications. SRILM is freely available for noncommercial purposes. The toolkit supports creation ..."
Abstract
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Cited by 1218 (21 self)
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SRILM is a collection of C++ libraries, executable programs, and helper scripts designed to allow both production of and experimentation with statistical language models for speech recognition and other applications. SRILM is freely available for noncommercial purposes. The toolkit supports
Building a Large Annotated Corpus of English: The Penn Treebank
- COMPUTATIONAL LINGUISTICS
, 1993
"... There is a growing consensus that significant, rapid progress can be made in both text understanding and spoken language understanding by investigating those phenomena that occur most centrally in naturally occurring unconstrained materials and by attempting to automatically extract information abou ..."
Abstract
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Cited by 2740 (10 self)
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for enterprises as diverse as the automatic construction of statistical models for the grammar of the written and the colloquial spoken language, the development of explicit formal theories of the differing grammars of writing and speech, the investigation of prosodic phenomena in speech, and the evaluation
A General Language Model for Information Retrieval
- In Proceedings of the 1999 ACM SIGIR Conference on Research and Development in Information Retrieval
, 1999
"... Statistical language modeling has been successfully used for speech recognition, part-of-speech tagging, and syntactic parsing. Recently, it has also been applied to information retrieval. According to this new paradigm, each document is viewed as a language sample, and a query as a generation proce ..."
Abstract
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Cited by 243 (15 self)
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Statistical language modeling has been successfully used for speech recognition, part-of-speech tagging, and syntactic parsing. Recently, it has also been applied to information retrieval. According to this new paradigm, each document is viewed as a language sample, and a query as a generation
Machine Learning Research: Four Current Directions
, 1997
"... Machine Learning research has been making great progress in many directions. This article summarizes four of these directions and discusses some current open problems. The four directions are (a) improving classification accuracy by learning ensembles of classifiers, (b) methods for scaling up super ..."
Abstract
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Cited by 287 (0 self)
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learning theory, neural networks, statistics, and pattern recognition have discovered one another and begun to work together. Second, machine learning techniques are being applied to new kinds of problems including knowledge discovery in databases, language processing, robot control, and combinatorial
Speech Recognition Experimental Results for Romanian Language
- Proceedings of ECIT2010 – The 6th European Conference on Intelligent Systems and Technologies, Iasi, Romania, 2010, CD, 13p, Invited Plenary Session I
"... Abstract. Automatic speech recognition in database-lacking languages like Romanian must imply new system designs or new methods in training state-of-the-art systems. We propose an innovative training strategy for Hidden Markov Models (HMM) based systems. It implies starting with isolated monophones ..."
Abstract
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Cited by 1 (1 self)
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Abstract. Automatic speech recognition in database-lacking languages like Romanian must imply new system designs or new methods in training state-of-the-art systems. We propose an innovative training strategy for Hidden Markov Models (HMM) based systems. It implies starting with isolated monophones
Two decades of statistical language modeling: Where do we go from here
- Proceedings of the IEEE
, 2000
"... Statistical Language Models estimate the distribution of various natural language phenomena for the purpose of speech recognition and other language technologies. Since the first significant model was proposed in 1980, many attempts have been made to improve the state of the art. We review them here ..."
Abstract
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Cited by 210 (1 self)
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Statistical Language Models estimate the distribution of various natural language phenomena for the purpose of speech recognition and other language technologies. Since the first significant model was proposed in 1980, many attempts have been made to improve the state of the art. We review them
The role of strong syllables in segmentation for lexical access
- Journal of Experimental Psychology: Human Perception and Performance
, 1988
"... A model of speech segmentation in a stress language is proposed, according to which the occurrence of a strong syllable triggers segmentation of the speech signal, whereas occurrence of a weak syllable does not trigger segmentation. We report experiments in which listeners detected words embedded in ..."
Abstract
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Cited by 250 (29 self)
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, it is segmented from the first syllable, and successful detection of the embedded word therefore requires assembly of speech material across a segmentation position. Speech recognition models involving phonemic or syllabic receding, or based on strictly left-to-right processes, do not predict this result
Continuous Speech Recognition Using Hidden Markov Models
- IEEE ASSP MAGAZINE
, 1990
"... Stochastic signal processing techniques have pro-foundly changed our perspective on speech processing. We have witnessed a progression from heuristic algo-rithms to detailed statistical approaches based on itera-t ive analysis techniques. Markov modeling provides a mathematically rigorous approach t ..."
Abstract
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Cited by 54 (9 self)
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Stochastic signal processing techniques have pro-foundly changed our perspective on speech processing. We have witnessed a progression from heuristic algo-rithms to detailed statistical approaches based on itera-t ive analysis techniques. Markov modeling provides a mathematically rigorous approach
Hidden Markov ModelBased Speech Emotion Recognition
- Proceedings of the ICASSP 2003, IEEE
, 2003
"... In this contribution we intro duce speech emotion recognition by use of continuous hidden Markov models. Two methods are propagated and compared throughout the paper. Within the first method a global statistics framework of an utterance is classified by Gaussian mixture models using derived features ..."
Abstract
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Cited by 75 (24 self)
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In this contribution we intro duce speech emotion recognition by use of continuous hidden Markov models. Two methods are propagated and compared throughout the paper. Within the first method a global statistics framework of an utterance is classified by Gaussian mixture models using derived
Results 1 - 10
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836
