Browsing by Author "Blaauw, Merlijn"

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  • Blaauw, Merlijn; Bonada, Jordi, 1973- (International Speech Communication Association (ISCA), 2017)
    We present a new model for singing synthesis based on a modified version of the WaveNet architecture. Instead of modeling raw waveform, we model features produced by a parametric vocoder that separates the influence of ...
  • Blaauw, Merlijn; Bonada, Jordi, 1973- (MDPI, 2017)
    We recently presented a new model for singing synthesis based on a modified version of the WaveNet architecture. Instead of modeling raw waveform, we model features produced by a parametric vocoder that separates the ...
  • Chandna, Pritish; Blaauw, Merlijn; Bonada, Jordi, 1973-; Gómez Gutiérrez, Emilia, 1975- (Institute of Electrical and Electronics Engineers (IEEE), 2019)
    This paper presents a novel method for extracting the vocal track from a musical mixture. The musical mixture consists of a singing voice and a backing track which may comprise of various instruments. We use a convolutional ...
  • Bonada, Jordi, 1973-; Lachlan, Robert; Blaauw, Merlijn (International Speech Communication Association (ISCA), 2016)
    This paper focuses on the synthesis of bird songs using Hidden Markov Models (HMM). This technique has been widely used for speech modeling and synthesis. However, features and contextual factors typically used for human ...
  • 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 ...
  • 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 ...
  • Bonada, Jordi, 1973-; Umbert Morist, Martí; Blaauw, Merlijn (International Speech Communication Association (ISCA), 2016)
    Sample and statistically based singing synthesizers typically require a large amount of data for automatically generating expressive synthetic performances. In this paper we present a singing synthesizer that using two ...
  • 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 ...
  • 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 ...
  • Maestre Gómez, Esteban; Blaauw, Merlijn; Bonada, Jordi, 1973-; Guaus, Enric; Pérez Carrillo, Alfonso Antonio, 1977- (Institute of Electrical and Electronics Engineers (IEEE), 2010)
    Excitation-continuous music instrument control patterns are often not explicitly represented in current sound synthesis techniques when applied to automatic performance. Both physical model-based and sample-based synthesis ...
  • Chandna, Pritish; Blaauw, Merlijn; Bonada, Jordi, 1973-; Gómez Gutiérrez, Emilia, 1975- (Institute of Electrical and Electronics Engineers (IEEE), 2019)
    We present a deep neural network based singing voice synthesizer, inspired by the Deep Convolutions Generative Adversarial Networks (DCGAN) architecture and optimized using the Wasserstein-GAN algorithm. We use vocoder ...