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pro vyhledávání: '"Maimon, Gallil"'
Speech language models have recently demonstrated great potential as universal speech processing systems. Such models have the ability to model the rich acoustic information existing in audio signals, beyond spoken content, such as emotion, backgroun
Externí odkaz:
http://arxiv.org/abs/2409.07437
Backdoor poisoning attacks pose a well-known risk to neural networks. However, most studies have focused on lenient threat models. We introduce Silent Killer, a novel attack that operates in clean-label, black-box settings, uses a stealthy poison and
Externí odkaz:
http://arxiv.org/abs/2301.02615
Autor:
Maimon, Gallil, Adi, Yossi
We introduce DISSC, a novel, lightweight method that converts the rhythm, pitch contour and timbre of a recording to a target speaker in a textless manner. Unlike DISSC, most voice conversion (VC) methods focus primarily on timbre, and ignore people'
Externí odkaz:
http://arxiv.org/abs/2212.09730
Autor:
Maimon, Gallil, Rokach, Lior
Discovering the existence of universal adversarial perturbations had large theoretical and practical impacts on the field of adversarial learning. In the text domain, most universal studies focused on adversarial prefixes which are added to all texts
Externí odkaz:
http://arxiv.org/abs/2206.09458
We propose a stealthy and powerful backdoor attack on neural networks based on data poisoning (DP). In contrast to previous attacks, both the poison and the trigger in our method are stealthy. We are able to change the model's classification of sampl
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::63c8630d643f7e95ab5a43fce8248dfb
http://arxiv.org/abs/2301.02615
http://arxiv.org/abs/2301.02615
Autor:
Maimon, Gallil, Adi, Yossi
Voice Conversion (VC) is the task of making a spoken utterance by one speaker sound as if uttered by a different speaker, while keeping other aspects like content unchanged. Current VC methods, focus primarily on spectral features like timbre, while
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::d5f3a75a9d4871ed91df37e19d481d57