8 citations · 15 across the 33 of their papers we have counts for
5 papers · 1 filter
Articulatory Representation Learning Via Joint Factor Analysis and Neural Matrix Factorization
Jiachen Lian, Alan W Black, Yijing Lu +3
Articulatory representation learning is the fundamental research in modeling neural speech production system. Our previous work has established a deep paradigm to decompose the art…
Towards Improved Zero-shot Voice Conversion with Conditional DSVAE
Jiachen Lian, Chunlei Zhang, Gopala Krishna Anumanchipalli +1
Disentangling content and speaking style information is essential for zero-shot non-parallel voice conversion (VC). Our previous study investigated a novel framework with disentang…
Unsupervised TTS Acoustic Modeling for TTS with Conditional Disentangled Sequential VAE
Jiachen Lian, Chunlei Zhang, Gopala Krishna Anumanchipalli +1
In this paper, we propose a novel unsupervised text-to-speech acoustic model training scheme, named UTTS, which does not require text-audio pairs. UTTS is a multi-speaker speech sy…
Deep Neural Convolutive Matrix Factorization for Articulatory Representation Decomposition
Jiachen Lian, Alan W Black, Louis Goldstein +1
Most of the research on data-driven speech representation learning has focused on raw audios in an end-to-end manner, paying little attention to their internal phonological or gest…
Robust Disentangled Variational Speech Representation Learning for Zero-shot Voice Conversion
Jiachen Lian, Chunlei Zhang, Dong Yu
Traditional studies on voice conversion (VC) have made progress with parallel training data and known speakers. Good voice conversion quality is obtained by exploring better alignm…