55 citations · 111 across the 8 of their papers we have counts for
6 papers · 1 filter
Voice conversion with limited data and limitless data augmentations
Olga Slizovskaia, Jordi Janer, Pritish Chandna +1
Applying changes to an input speech signal to change the perceived speaker of speech to a target while maintaining the content of the input is a challenging but interesting task kn…
LoopNet: Musical Loop Synthesis Conditioned On Intuitive Musical Parameters
Pritish Chandna, António Ramires, Xavier Serra +1
Loops, seamlessly repeatable musical segments, are a cornerstone of modern music production. Contemporary artists often mix and match various sampled or pre-recorded loops based on…
A Vocoder Based Method For Singing Voice Extraction
Pritish Chandna, Merlijn Blaauw, Jordi Bonada +1
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…
A Framework for Multi-f0 Modeling in SATB Choir Recordings
Helena Cuesta, Emilia Gómez, Pritish Chandna
Fundamental frequency (f0) modeling is an important but relatively unexplored aspect of choir singing. Performance evaluation as well as auditory analysis of singing, whether indiv…
WGANSing: A Multi-Voice Singing Voice Synthesizer Based on the Wasserstein-GAN
Pritish Chandna, Merlijn Blaauw, Jordi Bonada +1
We present a deep neural network based singing voice synthesizer, inspired by the Deep Convolutions Generative Adversarial Networks (DCGAN) architecture and optimized using the Was…
Deep Learning for Singing Processing: Achievements, Challenges and Impact on Singers and Listeners
Emilia Gómez, Merlijn Blaauw, Jordi Bonada +2
This paper summarizes some recent advances on a set of tasks related to the processing of singing using state-of-the-art deep learning techniques. We discuss their achievements in…