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pro vyhledávání: '"Tilli, Pascal"'
Dual encoder architectures like CLIP models map two types of inputs into a shared embedding space and learn similarities between them. However, it is not understood how such models compare two inputs. Here, we address this research gap with two contr
Externí odkaz:
http://arxiv.org/abs/2408.14153
Autor:
Tilli, Pascal, Vu, Ngoc Thang
The large success of deep learning based methods in Visual Question Answering (VQA) has concurrently increased the demand for explainable methods. Most methods in Explainable Artificial Intelligence (XAI) focus on generating post-hoc explanations rat
Externí odkaz:
http://arxiv.org/abs/2403.17647
Customizing voice and speaking style in a speech synthesis system with intuitive and fine-grained controls is challenging, given that little data with appropriate labels is available. Furthermore, editing an existing human's voice also comes with eth
Externí odkaz:
http://arxiv.org/abs/2310.17502
In order to protect the privacy of speech data, speaker anonymization aims for hiding the identity of a speaker by changing the voice in speech recordings. This typically comes with a privacy-utility trade-off between protection of individuals and us
Externí odkaz:
http://arxiv.org/abs/2210.07002
In this work, we propose a speaker anonymization pipeline that leverages high quality automatic speech recognition and synthesis systems to generate speech conditioned on phonetic transcriptions and anonymized speaker embeddings. Using phones as the
Externí odkaz:
http://arxiv.org/abs/2207.04834
On the way towards general Visual Question Answering (VQA) systems that are able to answer arbitrary questions, the need arises for evaluation beyond single-metric leaderboards for specific datasets. To this end, we propose a browser-based benchmarki
Externí odkaz:
http://arxiv.org/abs/2110.05159
Autor:
Tilli, Pascal
Humans have the ability to continually acquire knowledge throughout their lifespan. In contrast, neural networks suffer from catastrophic forgetting when trained on new tasks. Continual learning studies the methods to achieve similar memory effects i
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::82953ab75cc751f9614f01122cfb71b5