Wael Hamza
Wael Hamza
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Cited by
Cited by
Bilateral multi-perspective matching for natural language sentences
Z Wang, W Hamza, R Florian
arXiv preprint arXiv:1702.03814, 2017
Generating paralinguistic phenomena via markup in text-to-speech synthesis
AS Aaron, R Bakis, EM Eide, W Hamza
US Patent 7,472,065, 2008
The IBM expressive text-to-speech synthesis system for American English
JF Pitrelli, R Bakis, EM Eide, R Fernandez, W Hamza, MA Picheny
IEEE Transactions on Audio, Speech, and Language Processing 14 (4), 1099-1108, 2006
Method, apparatus and computer program providing a multi-speaker database for concatenative text-to-speech synthesis
AS Aaron, EM Eide, WM Hamza, MA Picheny, CT Rutherfoord, ...
US Patent 7,716,052, 2010
Multi-perspective context matching for machine comprehension
Z Wang, H Mi, W Hamza, R Florian
arXiv preprint arXiv:1612.04211, 2016
Leveraging context information for natural question generation
L Song, Z Wang, W Hamza, Y Zhang, D Gildea
Proceedings of the 2018 Conference of the North American Chapter of the …, 2018
Methods and computer program products for providing paraphrasing in a text-to-speech system
R Bakis, EM Eide, W Hamza, MA Picheny
US Patent App. 11/619,682, 2008
Neural cross-lingual entity linking
A Sil, G Kundu, R Florian, W Hamza
Proceedings of the AAAI Conference on Artificial Intelligence 32 (1), 2018
A corpus-based approach to< ahem/> expressive speech synthesis
E Eide, A Aaron, R Bakis, W Hamza, M Picheny, J Pitrelli
5th ISCA Speech Synthesis Workshop, 79-84, 2004
Don’t parse, generate! a sequence to sequence architecture for task-oriented semantic parsing
S Rongali, L Soldaini, E Monti, W Hamza
Proceedings of the web conference 2020, 2962-2968, 2020
The IBM expressive speech synthesis system.
W Hamza, E Eide, R Bakis, M Picheny, JF Pitrelli
INTERSPEECH, 2577-2580, 2004
Systems and methods for text-to-speech synthesis using spoken example
A Aaron, R Bakis, EM Eide, WM Hamza
US Patent 8,886,538, 2014
A unified query-based generative model for question generation and question answering
L Song, Z Wang, W Hamza
arXiv preprint arXiv:1709.01058, 2017
Alexa teacher model: Pretraining and distilling multi-billion-parameter encoders for natural language understanding systems
J FitzGerald, S Ananthakrishnan, K Arkoudas, D Bernardi, A Bhagia, ...
Proceedings of the 28th ACM SIGKDD Conference on Knowledge Discovery and …, 2022
Alexatm 20b: Few-shot learning using a large-scale multilingual seq2seq model
S Soltan, S Ananthakrishnan, J FitzGerald, R Gupta, W Hamza, H Khan, ...
arXiv preprint arXiv:2208.01448, 2022
Recent improvements to the IBM trainable speech synthesis system
E Eide, A Aaron, R Bakis, R Cohen, R Donovan, W Hamza, T Mathes, ...
2003 IEEE International Conference on Acoustics, Speech, and Signal …, 2003
Current status of the IBM trainable speech synthesis system
R Donovan, A Ittycheriah, M Franz, B Ramabhadran, E Eide, ...
4th ISCA Tutorial and Research Workshop (ITRW) on Speech Synthesis, 2001
ASR n-best fusion nets
X Liu, M Li, L Chen, P Wanigasekara, W Ruan, H Khan, W Hamza, C Su
ICASSP 2021-2021 IEEE International Conference on Acoustics, Speech and …, 2021
Methods and apparatus for adapting output speech in accordance with context of communication
EM Eide, WM Hamza, MA Picheny
US Patent 7,490,042, 2009
Neural cross-lingual coreference resolution and its application to entity linking
G Kundu, A Sil, R Florian, W Hamza
arXiv preprint arXiv:1806.10201, 2018
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