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pro vyhledávání: '"Ibarrola, Francisco"'
Autor:
Ibarrola, Francisco, Grace, Kazjon
Quality and diversity have been proposed as reasonable heuristics for assessing content generated by co-creative systems, but to date there has been little agreement around what constitutes the latter or how to measure it. Proposed approaches for ass
Externí odkaz:
http://arxiv.org/abs/2403.13826
In creativity support and computational co-creativity contexts, the task of discovering appropriate prompts for use with text-to-image generative models remains difficult. In many cases the creator wishes to evoke a certain impression with the image,
Externí odkaz:
http://arxiv.org/abs/2302.09742
Recent advances in text-conditioned generative models have provided us with neural networks capable of creating images of astonishing quality, be they realistic, abstract, or even creative. These models have in common that (more or less explicitly) t
Externí odkaz:
http://arxiv.org/abs/2209.12588
Generative models are undoubtedly a hot topic in Artificial Intelligence, among which the most common type is Generative Adversarial Networks (GANs). These architectures let one synthesise artificial datasets by implicitly modelling the underlying pr
Externí odkaz:
http://arxiv.org/abs/2007.02845
Extreme Learning Machines (ELMs) have become a popular tool in the field of Artificial Intelligence due to their very high training speed and generalization capabilities. Another advantage is that they have a single hyper-parameter that must be tuned
Externí odkaz:
http://arxiv.org/abs/1912.02154
Akademický článek
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When recorded in an enclosed room, a sound signal will most certainly get affected by reverberation. This not only undermines audio quality, but also poses a problem for many human-machine interaction technologies that use speech as their input. In t
Externí odkaz:
http://arxiv.org/abs/1809.07375
When a signal is recorded in an enclosed room, it typically gets affected by reverberation. This degradation represents a problem when dealing with audio signals, particularly in the field of speech signal processing, such as automatic speech recogni
Externí odkaz:
http://arxiv.org/abs/1706.00114
A Bayesian approach to convolutive nonnegative matrix factorization for blind speech dereverberation
Publikováno v:
In Signal Processing October 2018 151:89-98
Publikováno v:
In Journal of Mathematical Analysis and Applications 1 June 2017 450(1):427-443