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Cristina España-Bonet
Researcher at German Research Centre for Artificial Intelligence
Publications - 73
Citations - 994
Cristina España-Bonet is an academic researcher from German Research Centre for Artificial Intelligence. The author has contributed to research in topics: Machine translation & Computer science. The author has an hindex of 14, co-authored 62 publications receiving 875 citations. Previous affiliations of Cristina España-Bonet include Polytechnic University of Catalonia & University of Barcelona.
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Journal ArticleDOI
Variable cosmological constant as a Planck scale effect
TL;DR: In this paper, a semiclassical Friedmann-Lemaitre-Robertson-Walker (FLRW) cosmological model was proposed to predict an increase of 10-20% in the value of Ω Λ at redshifts z = 1-1.5 perfectly reachable by SNAP.
Journal ArticleDOI
Testing the running of the cosmological constant with type Ia supernovae at high z
TL;DR: In this article, the authors further developed the cosmological consequences of a ''running constant'' by addressing the accelerated evolution of the universe within that model and showed that SNAP can probe the predicted variation of the CC either ruling out this idea or confirming the evolution hereafter expected.
Journal ArticleDOI
Testing the running of the cosmological constant with Type Ia Supernovae at high z
TL;DR: In this article, the authors further developed the cosmological consequences of a "running" constant evolving with time by addressing the accelerated evolution of the universe within that model, and showed that SNAP can probe the predicted variation of the CC either ruling out this idea or confirming the evolution hereafter expected.
Journal ArticleDOI
An Empirical Analysis of NMT-Derived Interlingual Embeddings and Their Use in Parallel Sentence Identification
TL;DR: This work systematically study the neural machine translation context vectors, i.e., output of the encoder, and their power as an interlingua representation of a sentence, and assess their quality and effectiveness by measuring similarities across translations, as well as semantically related and semantically unrelated sentence pairs.
Book ChapterDOI
Automatic Speech Recognition with Deep Neural Networks for Impaired Speech
TL;DR: A comparison between architectures shows that, even with a small database, hybrid DNN-HMM models outperform classical GMM-H MM according to word error rate measures.