758 citations · 984 across the 17 of their papers we have counts for
19 papers
Analyzing and Improving Speaker Similarity Assessment for Speech Synthesis
Marc-André Carbonneau, Benjamin van Niekerk, Hugo Seuté +3
Modeling voice identity is challenging due to its multifaceted nature. In generative speech systems, identity is often assessed using automatic speaker verification (ASV) embedding…
LinearVC: Linear transformations of self-supervised features through the lens of voice conversion
Herman Kamper, Benjamin van Niekerk, Julian Zaïdi +1
We introduce LinearVC, a simple voice conversion method that sheds light on the structure of self-supervised representations. First, we show that simple linear transformations of s…
Geometry-Aware Texture Generation for 3D Head Modeling with Artist-driven Control
Amin Fadaeinejad, Abdallah Dib, Luiz Gustavo Hafemann +6
Creating realistic 3D head assets for virtual characters that match a precise artistic vision remains labor-intensive. We present a novel framework that streamlines this process by…
SEREP: Semantic Facial Expression Representation for Robust In-the-Wild Capture and Retargeting
Arthur Josi, Luiz Gustavo Hafemann, Abdallah Dib +3
Monocular facial performance capture in-the-wild is challenging due to varied capture conditions, face shapes, and expressions. Most current methods rely on linear 3D Morphable Mod…
Spoken-Term Discovery using Discrete Speech Units
Benjamin van Niekerk, Julian Zaïdi, Marc-André Carbonneau +1
Discovering a lexicon from unlabeled audio is a longstanding challenge for zero-resource speech processing. One approach is to search for frequently occurring patterns in speech. W…
BinaryAlign: Word Alignment as Binary Sequence Labeling
Gaetan Lopez Latouche, Marc-André Carbonneau, Ben Swanson
Real world deployments of word alignment are almost certain to cover both high and low resource languages. However, the state-of-the-art for this task recommends a different model…
Zero-shot Cross-Lingual Transfer for Synthetic Data Generation in Grammatical Error Detection
Gaetan Lopez Latouche, Marc-André Carbonneau, Ben Swanson
Grammatical Error Detection (GED) methods rely heavily on human annotated error corpora. However, these annotations are unavailable in many low-resource languages. In this paper, w…
UPose3D: Uncertainty-Aware 3D Human Pose Estimation with Cross-View and Temporal Cues
Vandad Davoodnia, Saeed Ghorbani, Marc-André Carbonneau +2
We introduce UPose3D, a novel approach for multi-view 3D human pose estimation, addressing challenges in accuracy and scalability. Our method advances existing pose estimation fram…
MoSAR: Monocular Semi-Supervised Model for Avatar Reconstruction using Differentiable Shading
Abdallah Dib, Luiz Gustavo Hafemann, Emeline Got +4
Reconstructing an avatar from a portrait image has many applications in multimedia, but remains a challenging research problem. Extracting reflectance maps and geometry from one im…
EDMSound: Spectrogram Based Diffusion Models for Efficient and High-Quality Audio Synthesis
Ge Zhu, Yutong Wen, Marc-André Carbonneau +1
Audio diffusion models can synthesize a wide variety of sounds. Existing models often operate on the latent domain with cascaded phase recovery modules to reconstruct waveform. Thi…
Rhythm Modeling for Voice Conversion
Benjamin van Niekerk, Marc-André Carbonneau, Herman Kamper
Voice conversion aims to transform source speech into a different target voice. However, typical voice conversion systems do not account for rhythm, which is an important factor in…
ZeroEGGS: Zero-shot Example-based Gesture Generation from Speech
Saeed Ghorbani, Ylva Ferstl, Daniel Holden +2
We present ZeroEGGS, a neural network framework for speech-driven gesture generation with zero-shot style control by example. This means style can be controlled via only a short ex…
A Comparison of Discrete and Soft Speech Units for Improved Voice Conversion
Benjamin van Niekerk, Marc-André Carbonneau, Julian Zaïdi +3
The goal of voice conversion is to transform source speech into a target voice, keeping the content unchanged. In this paper, we focus on self-supervised representation learning fo…
Daft-Exprt: Cross-Speaker Prosody Transfer on Any Text for Expressive Speech Synthesis
Julian Zaïdi, Hugo Seuté, Benjamin van Niekerk +1
This paper presents Daft-Exprt, a multi-speaker acoustic model advancing the state-of-the-art for cross-speaker prosody transfer on any text. This is one of the most challenging, a…
Energy Disaggregation using Variational Autoencoders
Antoine Langevin, Marc-André Carbonneau, Mohamed Cheriet +1
Non-intrusive load monitoring (NILM) is a technique that uses a single sensor to measure the total power consumption of a building. Using an energy disaggregation method, the consu…
Measuring Disentanglement: A Review of Metrics
Marc-André Carbonneau, Julian Zaidi, Jonathan Boilard +1
Learning to disentangle and represent factors of variation in data is an important problem in AI. While many advances have been made to learn these representations, it is still unc…
Bag-Level Aggregation for Multiple Instance Active Learning in Instance Classification Problems
Marc-André Carbonneau, Eric Granger, Ghyslain Gagnon
A growing number of applications, e.g. video surveillance and medical image analysis, require training recognition systems from large amounts of weakly annotated data while some ta…
Multiple Instance Learning: A Survey of Problem Characteristics and Applications
Marc-André Carbonneau, Veronika Cheplygina, Eric Granger +1
Multiple instance learning (MIL) is a form of weakly supervised learning where training instances are arranged in sets, called bags, and a label is provided for the entire bag. Thi…
Feature Learning from Spectrograms for Assessment of Personality Traits
Marc-André Carbonneau, Eric Granger, Yazid Attabi +1
Several methods have recently been proposed to analyze speech and automatically infer the personality of the speaker. These methods often rely on prosodic and other hand crafted sp…