1 citations · 1 across the 12 of their papers we have counts for
7 papers · 1 filter
Scaling Multi-Talker ASR with Speaker-Agnostic Activity Streams
Xiluo He, Alexander Polok, Jesús Villalba +2
An increasingly common training paradigm for multi-talker automatic speech recognition (ASR) is to use speaker activity signals to adapt single-speaker ASR models for overlapping s…
MaskVCT: Masked Voice Codec Transformer for Zero-Shot Voice Conversion With Increased Controllability via Multiple Guidances
Junhyeok Lee, Helin Wang, Yaohan Guan +4
We introduce MaskVCT, a zero-shot voice conversion (VC) model that offers multi-factor controllability through multiple classifier-free guidances (CFGs). While previous VC models r…
CA-SSLR: Condition-Aware Self-Supervised Learning Representation for Generalized Speech Processing
Yen-Ju Lu, Jing Liu, Thomas Thebaud +4
We introduce Condition-Aware Self-Supervised Learning Representation (CA-SSLR), a generalist conditioning model broadly applicable to various speech-processing tasks. Compared to s…
Noise-robust Speech Separation with Fast Generative Correction
Helin Wang, Jesus Villalba, Laureano Moro-Velazquez +3
Speech separation, the task of isolating multiple speech sources from a mixed audio signal, remains challenging in noisy environments. In this paper, we propose a generative correc…
Leveraging Pretrained Image-text Models for Improving Audio-Visual Learning
Saurabhchand Bhati, Jesús Villalba, Laureano Moro-Velazquez +2
Visually grounded speech systems learn from paired images and their spoken captions. Recently, there have been attempts to utilize the visually grounded models trained from images…
DuTa-VC: A Duration-aware Typical-to-atypical Voice Conversion Approach with Diffusion Probabilistic Model
Helin Wang, Thomas Thebaud, Jesus Villalba +4
We present a novel typical-to-atypical voice conversion approach (DuTa-VC), which (i) can be trained with nonparallel data (ii) first introduces diffusion probabilistic model (iii)…
Self-FiLM: Conditioning GANs with self-supervised representations for bandwidth extension based speaker recognition
Saurabh Kataria, Jesús Villalba, Laureano Moro-Velázquez +2
Speech super-resolution/Bandwidth Extension (BWE) can improve downstream tasks like Automatic Speaker Verification (ASV). We introduce a simple novel technique called Self-FiLM to…