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pro vyhledávání: '"Blanco, José"'
We present a novel neural encoder system for acoustic-to-articulatory inversion. We leverage the Pink Trombone voice synthesizer that reveals articulatory parameters (e.g tongue position and vocal cord configuration). Our system is designed to identi
Externí odkaz:
http://arxiv.org/abs/2406.14379
Autor:
Sánchez, María, Fernández, Laura, Arias, Julián, Cámara, Mateo, Comini, Giulia, Gabrys, Adam, Blanco, José Luis, Godino, Juan Ignacio, Hernández, Luis Alfonso
Recent advances in image, video, text and audio generative techniques, and their use by the general public, are leading to new forms of content generation. Usually, each modality was approached separately, which poses limitations. The automatic sound
Externí odkaz:
http://arxiv.org/abs/2402.01385
Since the energy domain is in a transformative shift towards sustainability, the integration of new technologies and smart systems into traditional power grids has emerged. As an effective approach, Petri Nets (PN) have been applied to model and anal
Externí odkaz:
http://arxiv.org/abs/2401.05462
Autor:
Cámara, Mateo, Blanco, José Luis
In this research, we present an interface based on Variational Autoencoders trained with a wide range of natural sounds for the innovative creation of Foley effects. The model can transfer new sound features to prerecorded audio or microphone-capture
Externí odkaz:
http://arxiv.org/abs/2310.15663
Dependence on raw materials, especially in the mining sector, is a key part of today's economy. Aggregates are vital, being the second most used raw material after water. Digitally transforming this sector is key to optimizing operations. However, su
Externí odkaz:
http://arxiv.org/abs/2310.16140
We present a non-supervised approach to optimize and evaluate the synthesis of non-speech audio effects from a speech production model. We use the Pink Trombone synthesizer as a case study of a simplified production model of the vocal tract to target
Externí odkaz:
http://arxiv.org/abs/2309.14761