• Data efficient voice cloning for neural singing synthesis

  Blaauw, Merlijn; Bonada, Jordi, 1973-; Daido, Ryunosuke (Institute of Electrical and Electronics Engineers (IEEE), 2019)

  There are many use cases in singing synthesis where creating voices from small amounts of data is desirable. In text-to-speech there have been several promising results that apply voice cloning techniques to modern deep ...
• Joint TV-L1 optical flow and occlusion estimation

  Garamendi, Juan Francisco; Lazcano, Vanel; Ballester, Coloma (IPOL, 2019)

  This document describes an implementation of the energy functional minimization proposed by Ballester, Garrido, Lazcano and Caselles for joint optical flow and occlusion estimation. The method build up from the ideas behind ...
• Feed-forward information and zero-lag synchronization in the sensory thalamocortical circuit are modulated during stimulus perception

  Tauste Campo, Adrià; Vázquez, Yuriria; Álvarez, Manuel; Zainos, Antonio; Rossi-Pool, Román; Deco, Gustavo; Romo, Ranulfo (National Academy of Sciences, 2019)

  The direction of functional information flow in the sensory thalamocortical circuit may play a role in stimulus perception, but, surprisingly, this process is poorly understood. We addressed this problem by evaluating a ...
• Color illusions also deceive CNNs for low-level vision tasks: analysis and implications

  Gómez Villa, Alexander; Martín, Adrian; Vazquez-Corral, Javier; Bertalmío, Marcelo; Malo, Jesús (Elsevier, 2020)

  The study of visual illusions has proven to be a very useful approach in vision science. In this work we start by showing that, while convolutional neural networks (CNNs) trained for low-level visual tasks in natural ...
• Evaluation of audio-based feedback technologies for bow learning technique in violin beginners

  Blanco, Angel David; Ramírez, Rafael,1966- (ACM Association for Computer Machinery, 2017)

  We present a study of the effects of feedback technologies on the learning process of novice violin students. Twenty-one subjects participated in our experiment, divided into two groups: Beginners (participants with no ...
• Participatory design methods to define educational goals for full-body interaction

  Schaper, Marie-Monique; Malinverni, Laura; Parés, Narcís, 1966- (ACM Association for Computer Machinery, 2014)

  The paper presents an exploratory study aimed toward including children in the design of an Interactive Learning Environment based on Full-Body Interaction. The study proposes a method based on using Participatory Design ...
• Coding for two-user energy harvesting interference channel

  Dabirnia, Mehdi; Duman, Tolga M. (Institute of Electrical and Electronics Engineers (IEEE), 2020)

  A two-user interference channel with energy harvesting transmitters, each equipped with a finite battery, is considered. Achievable rate regions (ARRs) considering independent and identically distributed Shannon strategies ...
• Mixed reality, full-body interactive experience to encourage cocial initiation for autism: comparison with a control nondigital intervention

  Crowell, Ciera; Sayis, Batuhan; Benitez, Juan Pablo; Parés, Narcís, 1966- (Mary Ann Liebert, Inc, 2020)

  Despite a proliferation in digital intervention tools for autism, many studies lack comparison with standard intervention tools, and are not evaluated with objective and standardized measures. In this article, we present ...
• Structuring collaboration: Multi-user full-body interaction environments for children with Autism Spectrum Disorder

  Crowell, Ciera; Mora-Guiard, Joan; Parés, Narcís, 1966- (Elsevier, 2019)

  Background Collaboration is an interpersonal process which builds upon social skills and mutual understanding. Due to characteristic social challenges, children with Autism Spectrum Disorders may benefit from structured ...
• Computing hierarchical finite state controllers with classical planning

  Segovia-Aguas, Javier; Jiménez, Sergio; Jonsson, Anders, 1973- (AI Access Foundation, 2018)

  Finite State Controllers (FSCs) are an effective way to compactly represent sequential plans. By imposing appropriate conditions on transitions, FSCs can also represent generalized plans (plans that solve a range of planning ...
• Seizure cycles in focal epilepsy

  Leguia, Marc G.; Andrzejak, Ralph Gregor; Rummel, Christian; Fan, Joline M.; Mirro, Emily A.; Tcheng, Thomas K.; Rao, Vikram R.; Baud, Maxime O. (American Medical Association, 2021)

  IMPORTANCE Focal epilepsy is characterized by the cyclical recurrence of seizures, but, to our knowledge, the prevalence and patterns of seizure cycles are unknown. OBJECTIVE To establish the prevalence, strength, and ...
• A reevaluation of Whittle (1986, 1992) reveals the link between detection thresholds, discrimination thresholds, and brightness perception

  Kane, David; Bertalmío, Marcelo (Association for Research in Vision and Ophthalmology (ARVO), 2019)

  In 1986, Paul Whittle investigated the ability to discriminate between the luminance of two small patches viewed upon a uniform background. In 1992, Paul Whittle asked subjects to manipulate the luminance of a number of ...
• Mitigating the impact of the novel coronavirus pandemic on neuroscience and music research protocols in clinical populations

  Papatzikis, Efthymios; Zeba, Fathima; Särkämö, Teppo; Ramírez, Rafael,1966-; Grau-Sánchez, Jennifer; Tervaniemi, Mari; Loewy, Joanne (Frontiers, 2020)

  The COVID-19 disease and the systemic responses to it has impacted lives, routines and procedures at an unprecedented level. While medical care and emergency response present immediate needs, the implications of this ...
• Applying deep learning techniques to estimate patterns of musical gesture

  Dalmazzo, David; Waddell, George; Ramírez, Rafael,1966- (Frontiers, 2021)

  Repetitive practice is one of the most important factors in improving the performance of motor skills. This paper focuses on the analysis and classification of forearm gestures in the context of violin playing. We recorded ...
• Re-Identification and growth detection of pulmonary nodules without image registration using 3D siamese neural networks

  Rafael Palou, Xavier; Aubanell, Anton; Bonavita, Ilaria; Ceresa, Mario; Piella Fenoy, Gemma; Ribas, Vicent; González Ballester, Miguel Ángel, 1973- (Elsevier, 2020)

  Lung cancer follow-up is a complex, error prone, and time consuming task for clinical radiologists. Several lung CT scan images taken at different time points of a given patient need to be individually inspected, looking ...
• Accurate and scalable version identification using musically-motivated embeddings

  Yesiler, Furkan; Serrà Julià, Joan; Gómez Gutiérrez, Emilia, 1975- (Institute of Electrical and Electronics Engineers (IEEE), 2020)

  The version identification (VI) task deals with the automatic detection of recordings that correspond to the same underlying musical piece. Despite many efforts, VI is still an open problem, with much room for improvement, ...
• Neural percussive synthesis parameterised by high-level timbral features

  Ramires, António; Chandna, Pritish; Favory, Xavier; Gómez Gutiérrez, Emilia, 1975-; Serra, Xavier (Institute of Electrical and Electronics Engineers (IEEE), 2020)

  We present a deep neural network-based methodology for synthesising percussive sounds with control over high-level timbral characteristics of the sounds. This approach allows for intuitive control of a synthesizer, enabling ...
• Sequence-to-sequence singing synthesis using the feed-forward transformer

  Blaauw, Merlijn; Bonada, Jordi, 1973- (Institute of Electrical and Electronics Engineers (IEEE), 2020)

  We propose a sequence-to-sequence singing synthesizer, which avoids the need for training data with pre-aligned phonetic and acoustic features. Rather than the more common approach of a content-based attention mechanism ...
• Content based singing voice extraction from a musical mixture

  Chandna, Pritish; Blaauw, Merlijn; Bonada, Jordi, 1973-; Gómez Gutiérrez, Emilia, 1975- (Institute of Electrical and Electronics Engineers (IEEE), 2020)

  We present a deep learning based methodology for extracting the singing voice signal from a musical mixture based on the underlying linguistic content. Our model follows an encoder-decoder architecture and takes as input ...
• Tensorflow audio models in Essentia

  Alonso-Jiménez, Pablo; Bogdanov, Dmitry; Pons Puig, Jordi; Serra, Xavier (Institute of Electrical and Electronics Engineers (IEEE), 2020)

  Essentia is a reference open-source C ++ /Python library for audio and music analysis. In this work, we present a set of algorithms that employ TensorFlow in Essentia, allow predictions with pre-trained deep learning models, ...

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