Browsing by Author "Miron, Marius"

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  • Serrà Julià, Joan; Koduri, Gopala Krishna; Miron, Marius; Serra, Xavier (International Society for Music Information Retrieval (ISMIR), 2011)
    The issue of tuning in Indian classical music has been, historically,/na matter of theoretical debate. In this paper, we/nstudy its contemporary practice in sung performances of Carnatic/nand Hindustani music following an ...
  • Koduri, Gopala Krishna; Miron, Marius; Serrà Julià, Joan; Serra, Xavier (International Society for Music Information Retrieval (ISMIR), 2011)
    The classical music traditions of the Indian subcontinent,/nHindustani and Carnatic, offer an excellent ground on which/nto test the limitations of current music information research/napproaches. At the same time, studies ...
  • Martel Baro, Héctor; Miron, Marius (2017)
    Training deep learning source separation methods involves computationally intensive procedures relying on large multi-track datasets. In this paper we use data augmentation to improve hip hop source sepa- ration using ...
  • Miron, Marius; Janer Mestres, Jordi; Gómez Gutiérrez, Emilia, 1975- (Aalto University, 2017)
    Deep learning approaches have become increasingly popular in estimating time-frequency masks for audio source separation. However, training neural networks usually requires a considerable amount of data. Music data is ...
  • Janer Mestres, Jordi; Gómez Gutiérrez, Emilia, 1975-; Martorell Domínguez, Agustín; Miron, Marius; de Wit, Benjamin (Institute of Electrical and Electronics Engineers (IEEE), 2016)
    This paper combines Audio Signal Processing and Virtual Reality (VR) content to create novel immersive experiences for orchestral music audiences. In VR, the auralization of sound sources of recorded live content remains ...
  • Dzhambazov, Georgi Bogomilov; Miron, Marius; Serra, Xavier (International Society for Music Information Retrieval (ISMIR), 2016)
    In this paper we describe an algorithm for automatic lyricsto-audio alignment. It has as a goal the automatic detection of word boundaries in multi-instrumental English pop songs. We rely on a phonetic recognizer based ...
  • Dzhambazov, Georgi Bogomilov; Miron, Marius; Serra, Xavier (International Society for Music Information Retrieval (ISMIR), 2016)
    In this paper we describe the two algorithms we submitted for the MIREX 2017 task of Automatic Lyrics-to-Audio Alignment. The task has as a goal the automatic detection of word boundaries in multi-instrumental English ...
  • 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 ...
  • 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 ...
  • Serrà, Joan; Surís, Dídac; Miron, Marius; Karatzoglou, Alexandros (Proceedings of Machine Learning Research, 2018)
    Catastrophic forgetting occurs when a neural network loses the information learned in a previous task after training on subsequent tasks. This problem remains a hurdle for artificial intelligence systems with sequential ...
  • Miron, Marius; Carabias Orti, Julio J.; Bosch, Juan J.; Gómez Gutiérrez, Emilia, 1975-; Janer Mestres, Jordi (Hindawi, 2016)
    This paper proposes a system for score-informed audio source separation for multichannel orchestral recordings. The orchestral music repertoire relies on the existence of scores. Thus, a reliable separation requires a good ...
  • Miron, Marius (Universitat Pompeu Fabra, 2018-02-08)
    Humans are able to distinguish between various sound sources in their environment and selectively attend to specific ones. However, it is a difficult task to teach a computer to automatically separate the acoustic scene ...