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检索条件"机构=Pattern Recognition and Human Language Technology"
382 条 记 录,以下是311-320 订阅
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EXPLOITING SPARSENESS OF BACKING-OFF language MODELS FOR EFFICIENT LOOK-AHEAD IN LVCSR
EXPLOITING SPARSENESS OF BACKING-OFF LANGUAGE MODELS FOR EFF...
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IEEE International Conference on Acoustics, Speech and Signal Processing
作者: David Nolden Hermann Ney Ralf Schluter Human Language Technology and Pattern Recognition GroupRWTH Aachen University Aachen Germany
In this paper, we propose a new method for computing and applying language model look-ahead in a dynamic network decoder, exploiting the sparseness of backing-off n-gram language models. Only partial (sparse) look-ahe... 详细信息
来源: 评论
THE RWTH 2010 QUAERO ASR EVALUATION SYSTEM FOR ENGLISH, FRENCH, AND GERMAN
THE RWTH 2010 QUAERO ASR EVALUATION SYSTEM FOR ENGLISH, FREN...
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IEEE International Conference on Acoustics, Speech and Signal Processing
作者: M. Sundermeyer M. Nussbaum-Thom S. Wiesler C. Plahl A. El-Desoky Mousa S. Hahn D. Nolden R. Schluter H. Ney Human Language Technology and Pattern Recognition Computer Science Department RWTH Aachen University
Recognizing Broadcast Conversational (BC) speech data is a difficult task, which can be regarded as one of the major challenges beyond the recognition of Broadcast News (BN). This paper presents the automatic speech r... 详细信息
来源: 评论
A comparative analysis of dynamic network decoding
A comparative analysis of dynamic network decoding
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International Conference on Acoustics, Speech, and Signal Processing (ICASSP)
作者: David Rybach Ralf Schlüter Hermann Ney Human Language Technology and Pattern Recognition Computer Science Department RWTH Aachen University Aachen Germany
The use of statically compiled search networks for ASR systems using huge vocabularies and complex language models often becomes challenging in terms of memory requirements. Dynamic network decoders introduce addition... 详细信息
来源: 评论
Powerful extensions to CRFS for grapheme to phoneme conversion
Powerful extensions to CRFS for grapheme to phoneme conversi...
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International Conference on Acoustics, Speech, and Signal Processing (ICASSP)
作者: Stefan Hahn Patrick Lehnen Hermann Ney Human Language Technology and Pattern Recognition Computer Science Department RWTH Aachen University Aachen Germany
Conditional Random Fields (CRFs) have proven to per form well on natural language processing tasks like name transliteration, concept tagging or grapheme-to-phoneme (g2p) conversion. The aim of this paper is to propos... 详细信息
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Hierarchical hybrid MLP/HMM or rather MLP features for a discriminatively trained Gaussian HMM: A comparison for offline handwriting recognition
Hierarchical hybrid MLP/HMM or rather MLP features for a dis...
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IEEE International Conference on Image Processing
作者: Philippe Dreuw Patrick Doetsch Christian Plahl Hermann Ney Human Language Technology and Pattern Recognition Computer Science Department RWTH Aachen University Aachen Germany
We use neural network based features extracted by a hierarchical multilayer-perceptron (MLP) network either in a hybrid MLP/HMM approach or to discriminatively retrain a Gaussian hidden Markov model (GHMM) system in a... 详细信息
来源: 评论
EM-style optimization of hidden conditional random fields for grapheme-to-phoneme conversion
EM-style optimization of hidden conditional random fields fo...
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International Conference on Acoustics, Speech, and Signal Processing (ICASSP)
作者: Georg Heigold Stefan Hahn Patrick Lehnen Hermann Ney Human Language Technology and Pattern Recognition Computer Science Department RWTH Aachen University Aachen Germany
We have recently proposed an EM-style algorithm to optimize log-linear models with hidden variables. In this paper, we use this algorithm to optimize a hidden conditional random field, i.e., a conditional random field... 详细信息
来源: 评论
Feature selection for log-linear acoustic models
Feature selection for log-linear acoustic models
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International Conference on Acoustics, Speech, and Signal Processing (ICASSP)
作者: S. Wiesler A. Richard Y. Kubo R. Schlüter H. Ney Human Language Technology and Pattern Recognition Computer Science Department RWTH Aachen University Aachen Germany
Log-linear acoustic models have been shown to be competitive with Gaussian mixture models in speech recognition. Their high training time can be reduced by feature selection. We compare a simple univariate feature sel... 详细信息
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Incorporating alignments into Conditional Random Fields for grapheme to phoneme conversion
Incorporating alignments into Conditional Random Fields for ...
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International Conference on Acoustics, Speech, and Signal Processing (ICASSP)
作者: Patrick Lehnen Stefan Hahn Andreas Guta Hermann Ney Human Language Technology and Pattern Recognition Computer Science Department RWTH Aachen University Aachen Germany
Conditional Random Fields (CRFs) are a state-of-the-art approach to natural language processing tasks like grapheme-to phoneme (g2p) conversion which is used to produce pronunciations or pronunciation variants for alm... 详细信息
来源: 评论
Non-stationary feature extraction for automatic speech recognition
Non-stationary feature extraction for automatic speech recog...
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International Conference on Acoustics, Speech, and Signal Processing (ICASSP)
作者: Zoltán Tüske Pavel Golik Ralf Schlüter Friedhelm R. Drepper Human Language Technology and Pattern Recognition Computer Science Department RWTH Aachen University Aachen Germany Zentralinstitut für Elektronik Forschungszentrum Jülich (KFA) Julich Germany
In current speech recognition systems mainly Short-Time Fourier Transform based features like MFCC are applied. Dropping the short-time stationarity assumption of the voiced speech, this paper introduces the non-stati... 详细信息
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Warp that smile on your face: Optimal and smooth deformations for face recognition
Warp that smile on your face: Optimal and smooth deformation...
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International Conference on Automatic Face and Gesture recognition
作者: Tobias Gass Leonid Pishchulin Philippe Dreuw Hermann Ney Human Language Technology and Pattern Recognition Group RWTH Aachen University Germany Computer Vision Laboratory ETH Zurich Switzerland Computer Vision and Multimodal Computing MPI Informatics Saarbruecken Germany
In this work, we present novel warping algorithms for full 2D pixel-grid deformations for face recognition. Due to high variation in face appearance, face recognition is considered a very difficult task, especially if... 详细信息
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