activity
20172022
collaborators

9 papers

cs.SD2022

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…

eess.AS2022

Locate This, Not That: Class-Conditioned Sound Event DOA Estimation

Olga Slizovskaia, Gordon Wichern, Zhong-Qiu Wang +1

Existing systems for sound event localization and detection (SELD) typically operate by estimating a source location for all classes at every time instant. In this paper, we propos…

eess.AS2020

Solos: A Dataset for Audio-Visual Music Analysis

Juan F. Montesinos, Olga Slizovskaia, Gloria Haro

In this paper, we present a new dataset of music performance videos which can be used for training machine learning methods for multiple tasks such as audio-visual blind source sep…

cs.SD2020

Conditioned Source Separation for Music Instrument Performances

Olga Slizovskaia, Gloria Haro, Emilia Gómez

In music source separation, the number of sources may vary for each piece and some of the sources may belong to the same family of instruments, thus sharing timbral characteristics…

eess.AS2020

Vocoder-Based Speech Synthesis from Silent Videos

Daniel Michelsanti, Olga Slizovskaia, Gloria Haro +3

Both acoustic and visual information influence human perception of speech. For this reason, the lack of audio in a video sequence determines an extremely low speech intelligibility…

cs.LG2019

Input complexity and out-of-distribution detection with likelihood-based generative models

Joan Serrà, David Álvarez, Vicenç Gómez +3

Likelihood-based generative models are a promising resource to detect out-of-distribution (OOD) inputs which could compromise the robustness or reliability of a machine learning sy…