Browsing by Author "Chandna, Pritish"

Sort by: Order: Results:

  • A deep-learning based framework for source separation, analysis, and synthesis of choral ensembles
    Chandna, Pritish; Cuesta, Helena; Petermann, Darius; Gómez Gutiérrez, Emilia, 1975- (Frontiers, 2022)
    Choral singing in the soprano, alto, tenor and bass (SATB) format is a widely practiced and studied art form with significant cultural importance. Despite the popularity of the choral setting, it has received little attention ...
  • A Framework for multi-f0 modeling in SATB choir recordings
    Cuesta, Helena; Gómez Gutiérrez, Emilia, 1975-; Chandna, Pritish (Sound and Music Computing, 2019)
    Fundamental frequency (f0) modeling is an important but relatively unexplored aspect of choir singing. Performance evaluation as well as auditory analysis of singing, whether individually or in a choir, often depend on ...
  • A Vocoder based method for singing voice extraction
    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 ...
  • 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 ...
  • A deep learning based analysis-synthesis framework for unison singing
    Chandna, Pritish; Cuesta, Helena; Gómez Gutiérrez, Emilia, 1975- (International Society for Music Information Retrieval (ISMIR), 2020)
    Unison singing is the name given to an ensemble of singers simultaneously singing the same melody and lyrics. While each individual singer in a unison sings the same principle melody, there are slight timing and pitch ...
  • Deep learning based source separation applied to choir ensembles
    Petermann, Darius; Chandna, Pritish; Cuesta, Helena; Bonada, Jordi, 1973-; Gómez Gutiérrez, Emilia, 1975- (International Society for Music Information Retrieval (ISMIR), 2020)
    Choral singing is a widely practiced form of ensemble singing wherein a group of people sing simultaneously in polyphonic harmony. The most commonly practiced setting for choir ensembles consists of four parts; Soprano, ...
  • Monoaural audio source separation using deep convolutional neural networks
    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 ...
  • Neural networks for singing voice extraction in monaural polyphonic music signals
    Chandna, Pritish (Universitat Pompeu Fabra, 2021-09-23)
    This thesis dissertation focuses on singing voice extraction from polyphonic musical signals. In particular, we focus on two cases; contemporary popular music, which typically has a processed singing voice with instrumental ...
  • 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 ...
  • WGansing: a multi-voice singing voice synthesizer based on the Wasserstein-Gan
    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 ...