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检索条件"机构=Human Language Technology And Pattern Recognition Group"
397 条 记 录,以下是141-150 订阅
排序:
Generative models for deep learning with very scarce data
arXiv
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arXiv 2019年
作者: Maroñas, Juan Paredes, Roberto Ramos, Daniel Pattern Recognition and Human Language Technology Universitat Politecnica de Valencia Valencia Spain AUDIAS Universidad Autonoma de Madrid Madrid Spain
The goal of this paper is to deal with a data scarcity scenario where deep learning techniques use to fail. We compare the use of two well established techniques, Restricted Boltzmann Machines and Variational Auto-enc... 详细信息
来源: 评论
Are automatic metrics robust and reliable in specific machine translation tasks?  21
Are automatic metrics robust and reliable in specific machin...
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21st Annual Conference of the European Association for Machine Translation, EAMT 2018
作者: Chinea-Rios, Mara Peris, Álvaro Casacuberta, Francisco Pattern Recognition and Human Language Technology Research Center Universitat Politècnica de València València Spain
We present a comparison of automatic metrics against human evaluations of translation quality in several scenarios which were unexplored up to now. Our experimentation was conducted on translation hypotheses that were... 详细信息
来源: 评论
Analysis of deep clustering as preprocessing for automatic speech recognition of sparsely overlapping speech
arXiv
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arXiv 2019年
作者: Menne, Tobias Sklyar, Ilya Schlüter, Ralf Ney, Hermann Human Language Technology and Pattern Recognition Computer Science Department RWTH Aachen University Aachen52074 Germany AppTek GmbH Aachen52062 Germany
Significant performance degradation of automatic speech recognition (ASR) systems is observed when the audio signal contains cross-talk. One of the recently proposed approaches to solve the problem of multi-speaker AS... 详细信息
来源: 评论
Active learning for interactive neural machine translation of data streams  22
Active learning for interactive neural machine translation o...
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22nd Conference on Computational Natural language Learning, CoNLL 2018
作者: Peris, Álvaro Casacuberta, Francisco Pattern Recognition and Human Language Technology Research Center Universitat Politècnica de València València Spain
We study the application of active learning techniques to the translation of unbounded data streams via interactive neural machine translation. The main idea is to select, from an unbounded stream of source sentences,... 详细信息
来源: 评论
LSTM language models for LVCSR in first-pass decoding and lattice-rescoring
arXiv
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arXiv 2019年
作者: Beck, Eugen Zhou, Wei Schlüter, Ralf Ney, Hermann Human Language Technology and Pattern Recognition Computer Science Department RWTH Aachen University Aachen52074 Germany AppTek GmbH Aachen52062 Germany
LSTM based language models are an important part of modern LVCSR systems as they significantly improve performance over traditional backoff language models. Incorporating them efficiently into decoding has been notori... 详细信息
来源: 评论
RWTH ASR Systems for LibriSpeech: Hybrid vs Attention - w/o Data Augmentation
arXiv
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arXiv 2019年
作者: Lüscher, Christoph Beck, Eugen Irie, Kazuki Kitza, Markus Michel, Wilfried Zeyer, Albert Schlüter, Ralf Ney, Hermann Human Language Technology and Pattern Recognition Computer Science Department RWTH Aachen University Aachen52074 Germany AppTek GmbH Aachen52062 Germany
We present state-of-the-art automatic speech recognition (ASR) systems employing a standard hybrid DNN/HMM architecture compared to an attention-based encoder-decoder design for the LibriSpeech task. Detailed descript... 详细信息
来源: 评论
Generating synthetic audio data for attention-based speech recognition systems
arXiv
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arXiv 2019年
作者: Rossenbach, Nick Zeyer, Albert Schlüter, Ralf Ney, Hermann Human Language Technology and Pattern Recognition Computer Science Department RWTH Aachen University Germany AppTek GmbH 52074 Aachen Aachen52062 Germany
Recent advances in text-to-speech (TTS) led to the development of flexible multi-speaker end-to-end TTS systems. We extend state-of-the-art attention-based automatic speech recognition (ASR) systems with synthetic aud... 详细信息
来源: 评论
Cumulative adaptation for BLSTM acoustic models
arXiv
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arXiv 2019年
作者: Kitza, Markus Golik, Pavel Schlüter, Ralf Ney, Hermann Human Language Technology and Pattern Recognition Computer Science Department RWTH Aachen University Aachen52074 Germany AppTek GmbH Aachen52062 Germany
This paper addresses the robust speech recognition problem as an adaptation task. Specifically, we investigate the cumulative application of adaptation methods. A bidirectional Long Short-Term Memory (BLSTM) based neu... 详细信息
来源: 评论
Modernizing Historical Documents: a User Study
arXiv
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arXiv 2019年
作者: Domingo, Miguel Casacuberta, Francisco Pattern Recognition and Human Language Technology Research Center Universitat Politècnica de València Camino de Vera s/n Valencia46022 Spain
Accessibility to historical documents is mostly limited to scholars. This is due to the language barrier inherent in human language and the linguistic properties of these documents. Given a historical document, modern... 详细信息
来源: 评论
Improved training of end-to-end attention models for speech recognition  19
Improved training of end-to-end attention models for speech ...
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19th Annual Conference of the International Speech Communication, INTERSPEECH 2018
作者: Zeyer, Albert Irie, Kazuki Schlüter, Ralf Ney, Hermann Human Language Technology and Pattern Recognition Computer Science Department RWTH Aachen University Aachen52062 Germany AppTek United States NNAISENSE Switzerland
Sequence-to-sequence attention-based models on subword units allow simple open-vocabulary end-to-end speech recognition. In this work, we show that such models can achieve competitive results on the Switchboard 300h a... 详细信息
来源: 评论