Georg Heigold
Georg Heigold
Research Scientist, Google Inc.
google.com의 이메일 확인됨 - 홈페이지
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An image is worth 16x16 words: Transformers for image recognition at scale
A Dosovitskiy, L Beyer, A Kolesnikov, D Weissenborn, X Zhai, ...
arXiv preprint arXiv:2010.11929, 2020
11552020
End-to-end text-dependent speaker verification
G Heigold, I Moreno, S Bengio, N Shazeer
2016 IEEE International Conference on Acoustics, Speech and Signal …, 2016
5332016
Small-footprint keyword spotting using deep neural networks
G Chen, C Parada, G Heigold
2014 IEEE International Conference on Acoustics, Speech and Signal …, 2014
4252014
Multilingual acoustic models using distributed deep neural networks
G Heigold, V Vanhoucke, A Senior, P Nguyen, MA Ranzato, M Devin, ...
2013 IEEE international conference on acoustics, speech and signal …, 2013
3252013
Word embeddings for speech recognition
S Bengio, G Heigold
1552014
An empirical study of learning rates in deep neural networks for speech recognition
A Senior, G Heigold, M Ranzato, K Yang
2013 IEEE international conference on acoustics, speech and signal …, 2013
1482013
Sequence discriminative distributed training of long short-term memory recurrent neural networks
H Sak, O Vinyals, G Heigold, A Senior, E McDermott, R Monga, M Mao
1452014
The RWTH Aachen University open source speech recognition system
D Rybach, C Gollan, G Heigold, B Hoffmeister, J Lööf, R Schlüter, H Ney
Tenth Annual Conference of the International Speech Communication Association, 2009
1302009
Object-centric learning with slot attention
F Locatello, D Weissenborn, T Unterthiner, A Mahendran, G Heigold, ...
arXiv preprint arXiv:2006.15055, 2020
892020
The RWTH 2007 TC-STAR evaluation system for european English and Spanish.
J Lööf, C Gollan, S Hahn, G Heigold, B Hoffmeister, C Plahl, D Rybach, ...
Interspeech, 2145-2148, 2007
792007
Asynchronous stochastic optimization for sequence training of deep neural networks
G Heigold, E McDermott, V Vanhoucke, A Senior, M Bacchiani
2014 IEEE International Conference on Acoustics, Speech and Signal …, 2014
722014
Modified MMI/MPE: A direct evaluation of the margin in speech recognition
G Heigold, T Deselaers, R Schlüter, H Ney
Proceedings of the 25th international conference on Machine learning, 384-391, 2008
642008
Multiframe deep neural networks for acoustic modeling
V Vanhoucke, M Devin, G Heigold
2013 IEEE International Conference on Acoustics, Speech and Signal …, 2013
582013
A linguistic evaluation of rule-based, phrase-based, and neural MT engines
A Burchardt, V Macketanz, J Dehdari, G Heigold, P Jan-Thorsten, ...
The Prague Bulletin of Mathematical Linguistics 108 (1), 159, 2017
562017
Discriminative training for automatic speech recognition: Modeling, criteria, optimization, implementation, and performance
G Heigold, H Ney, R Schluter, S Wiesler
IEEE Signal Processing Magazine 29 (6), 58-69, 2012
522012
Cross-lingual, Character-level neural morphological tagging
R Cotterell, G Heigold
arXiv preprint arXiv:1708.09157, 2017
512017
Vivit: A video vision transformer
A Arnab, M Dehghani, G Heigold, C Sun, M Lučić, C Schmid
arXiv preprint arXiv:2103.15691, 2021
502021
Equivalence of generative and log-linear models
G Heigold, H Ney, P Lehnen, T Gass, R Schluter
IEEE Transactions on Audio, Speech, and Language Processing 19 (5), 1138-1148, 2010
482010
A Gaussian mixture model layer jointly optimized with discriminative features within a deep neural network architecture
E Variani, E McDermott, G Heigold
2015 IEEE International Conference on Acoustics, Speech and Signal …, 2015
472015
A log-linear discriminative modeling framework for speech recognition
G Heigold
432010
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