Hochschulschrift
Handling multimodality and scarce resources in sign language machine translation
- Alternative title
-
Behandlung von Multimodalität und knappen Ressourcen in der maschinellen Gebärdensprachübersetzung
- Location
-
Deutsche Nationalbibliothek Frankfurt am Main
- Extent
-
Online-Ressource
- Language
-
Englisch
- Notes
-
RWTH Aachen University, Dissertation, 2016
- Classification
-
Sprache, Linguistik
- Event
-
Veröffentlichung
- (where)
-
Aachen
- (who)
-
Universitätsbibliothek der RWTH Aachen
- (when)
-
2016
- Creator
- Contributor
- URN
-
urn:nbn:de:hbz:82-rwth-2016-059732
- Rights
-
Der Zugriff auf das Objekt ist unbeschränkt möglich.
- Last update
-
25.03.2025, 1:41 PM CET
Data provider
This object is provided by:
Deutsche Nationalbibliothek. If you have any questions about the object, please contact the data provider.
Deutsche Nationalbibliothek. If you have any questions about the object, please contact the data provider.
Object type
- Hochschulschrift
Associated
- Schmidt, Christoph Andreas
- Ney, Hermann
- San-Segundo, Ruben
- Universitätsbibliothek der RWTH Aachen
Time of origin
- 2016
Other Objects (12)
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Exponentially Decaying Bag-of-Words Input Features for Feed-Forward Neural Network in Statistical Machine Translation
Language modeling and machine translation: improvements in training and modeling
Improving Unsupervised Word-by-Word Translation with Language Model and Denoising Autoencoder
Unsupervised training with applications in natural language processing
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Discriminative training of linear transformations and mixture density splitting for speech recognition
Generative Training and Smoothing of Hierarchical Phrase-Based Translation Models
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Automatic sign language recognition : from video corpora to gloss sentences
Towards large vocabulary continuous sign language recognition: from artificial to real-life tasks
Biasing Attention-Based Recurrent Neural Networks Using External Alignment Information
RETURNN as a Generic Flexible Neural Toolkit with Application to Translation and Speech Recognition
Exponentially Decaying Bag-of-Words Input Features for Feed-Forward Neural Network in Statistical Machine Translation
Language modeling and machine translation: improvements in training and modeling
Improving Unsupervised Word-by-Word Translation with Language Model and Denoising Autoencoder
Unsupervised training with applications in natural language processing
Alignment models for recurrent neural networks
Discriminative training of linear transformations and mixture density splitting for speech recognition
Generative Training and Smoothing of Hierarchical Phrase-Based Translation Models
Training and models for statistical machine translation
Automatic sign language recognition : from video corpora to gloss sentences
Towards large vocabulary continuous sign language recognition: from artificial to real-life tasks
Biasing Attention-Based Recurrent Neural Networks Using External Alignment Information
RETURNN as a Generic Flexible Neural Toolkit with Application to Translation and Speech Recognition
Exponentially Decaying Bag-of-Words Input Features for Feed-Forward Neural Network in Statistical Machine Translation
Language modeling and machine translation: improvements in training and modeling
Improving Unsupervised Word-by-Word Translation with Language Model and Denoising Autoencoder
Unsupervised training with applications in natural language processing
Alignment models for recurrent neural networks
Discriminative training of linear transformations and mixture density splitting for speech recognition
Generative Training and Smoothing of Hierarchical Phrase-Based Translation Models