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Visualitzant Congressos (Departament de Tecnologies de la Informació i les Comunicacions) per títol

Visualitzant Congressos (Departament de Tecnologies de la Informació i les Comunicacions) per títol

Ordena per: Ordre: Resultats:

  • Codina Filbà, Joan; Escalera, Sergio; Escudero, Joan; Antens, Coen; Buch-Cardona, Pau; Farrús, Mireia (Springer, 2021)
    People suffering Bipolar Disorder (BD) experiment changes in mood status having depressive or manic episodes with normal periods in the middle. BD is a chronic disease with a high level of non-adherence to medication that ...
  • Anantapadmanabhan, Akshay; Bellur, Ashwin; Murthy, Hema A. (Institute of Electrical and Electronics Engineers (IEEE), 2013)
    In this paper we use a Non-negative Matrix Factorization/n(NMF) based approach to analyze the strokes of the mri-/ndangam, a South Indian hand drum, in terms of the normal/nmodes of the instrument. Using ...
  • Serrà Julià, Joan; Kantz, Holger; Andrzejak, Ralph Gregor (ACM Association for Computer Machinery, 2010)
    Current systems for cover song detection are based on a model-free approach: they basically search for similarities in descriptor time series reflecting the evolution of tonal information in a musical piece. In this ...
  • Blaauw, Merlijn; Bonada, Jordi, 1973- (International Speech Communication Association (ISCA), 2016)
    Latent generative models can learn higher-level underlying factors from complex data in an unsupervised manner. Such models can be used in a wide range of speech processing applications, including synthesis, transformation ...
  • Pandey, Rahul; Castillo, Carlos; Purohit, Hemant (ACM Association for Computer Machinery, 2019)
    High-quality human annotations are necessary to create effective machine learning systems for social media. Low-quality human annotations indirectly contribute to the creation of inaccurate or biased learning systems. We ...
  • Dzhambazov, Georgi Bogomilov; Serra, Xavier (Music Technology Research Group, Department of Computer Science, Maynooth University, 2015)
    In this work we propose how to modify a standard scheme for text-to-speech alignment for the alignment of lyrics and singing voice. To this end we model the duration of phonemes specific for the case of singing. We rely ...
  • Miron, Marius; Janer Mestres, Jordi; Gómez Gutiérrez, Emilia, 1975- (International Society for Music Information Retrieval (ISMIR), 2017)
    Score information has been shown to improve music source separation when included into non-negative matrix factorization (NMF) frameworks. Recently, deep learning approaches have outperformed NMF methods in terms of ...
  • Chandna, Pritish; Miron, Marius; Janer Mestres, Jordi; Gómez Gutiérrez, Emilia, 1975- (Springer, 2017)
    In this paper we introduce a low-latency monaural source separation framework using a Convolutional Neural Network (CNN). We use a CNN to estimate time-frequency soft masks which are applied for source separation. We ...
  • Rezaeirowshan, Babak; Ballester, Coloma; Haro Ortega, Gloria (SCITEPRESS – Science and Technology Publications, Lda., 2016)
    In this paper we propose a method to estimate a global depth order between the objects of a scene using information from a single image coming from an uncalibrated camera. The method we present stems from early vision cues ...
  • Korzeniowski, Filip; Nieto Caballero, Oriol; McCallum, Matthew C.; Won, Minz; Oramas, Sergio; Schmidt, Erik M. (International Society for Music Information Retrieval (ISMIR), 2020)
    The mood of a song is a highly relevant feature for exploration and recommendation in large collections of music. These collections tend to require automatic methods for predicting such moods. In this work, we show that ...
  • Karakurt, Altug; Sentürk, Sertan; Serra, Xavier (ACM Association for Computer Machinery, 2016)
    In the general sense, mode defines the melodic framework and tonic acts as the reference tuning pitch for the melody in the performances of many music cultures. The mode and tonic information of the audio recordings is ...
  • Vujovic, Milica; Tassani, Simone; Hernández Leo, Davinia (Springer, 2019)
    In this paper, we describe an exploratory study where we investigate the possibilities of motion capture system as an instrument to consider in multi-modal analyses of face-to-face collaborative learning scenarios. The ...
  • Oliver, Maria; Raad, Lara; Ballester, Coloma; Haro Ortega, Gloria (Institute of Electrical and Electronics Engineers (IEEE), 2018)
    This work presents an automatic method for optical flow inpainting. Given a video, each frame domain is endowed with a Riemannian metric based on the video pixel values. The missing optical flow is recovered by solving the ...
  • Bellur, Ashwin; Ishwar, Vignesh; Murthy, Hema A. (Universitat Pompeu Fabra, 2012)
    A raga is a collective melodic expression consisting of motifs. A raga can be identified using motifs which are/nunique to it. Motifs can be thought of as signature prosodic phrases. Different ragas may be composed of the ...
  • Santos, Maria; Schaper, Marie-Monique; Parés, Narcís, 1966- (ACM Association for Computer Machinery, 2017)
    This paper presents a brief overview of the design and evaluation process of a Virtual Heritage (VH) experience for children in the context of Refugi 307, a bomb shelter built during the Spanish Civil War. The shelter ...
  • Celma Herrada, Òscar; Massaguer, Jordi; Cano Vila, Pedro; Gómez Gutiérrez, Emilia, 1975-; Gouyon, Fabien; Koppenberger, Markus; García, David (International Society for Music Information Retrieval (ISMIR), 2005)
    MUCOSA (Music Content Semantic Annotator) is an environment for the annotation and generation of music metadata at different levels of abstraction. It is composed of three tiers: an annotation client that deals with ...
  • Favory, Xavier; Serra, Xavier (2018)
    Recent advancements in web-based audio systems have enabled sufficiently accurate timing control and real-time sound processing capabilities. Numerous specialized music tools, as well as digital audio workstations, are ...
  • Ruiz Ovejero, Adrià; Rudovic, Ognjen; Binefa i Valls, Xavier; Pantic, Maja (Springer, 2017)
    In this paper, we address the Multi-Instance-Learning (MIL) problem when bag labels are naturally represented as ordinal variables (Multi-Instance-Ordinal Regression). Moreover, we consider the case where bags are temporal ...
  • Oramas, Sergio; Nieto Caballero, Oriol; Barbieri, Francesco; Serra, Xavier (International Society for Music Information Retrieval (ISMIR), 2017)
    Music genres allow to categorize musical items that share common characteristics. Although these categories are not mutually exclusive, most related research is traditionally focused on classifying tracks into a single ...
  • Accuosto, Pablo; Ronzano, Francesco; Ferrés, Daniel; Saggion, Horacio (ACM Association for Computer Machinery, 2017)
    We present a system to mine and visualize collections of scientific documents by semantically browsing information extracted from single publications or aggregated throughout corpora of articles. The text mining tool ...

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