2 citations · 2 across the 1 of their papers we have counts for
5 papers
Emilia: A Large-Scale, Extensive, Multilingual, and Diverse Dataset for Speech Generation
Haorui He, Zengqiang Shang, Chaoren Wang +11
Recent advancements in speech generation have been driven by large-scale training datasets. However, current models struggle to capture the spontaneity and variability inherent in…
SF-Speech: Straightened Flow for Zero-Shot Voice Clone
Xuyuan Li, Zengqiang Shang, Hua Hua +4
Recently, neural ordinary differential equations (ODE) models trained with flow matching have achieved impressive performance on the zero-shot voice clone task. Nevertheless, postu…
Emilia: An Extensive, Multilingual, and Diverse Speech Dataset for Large-Scale Speech Generation
Haorui He, Zengqiang Shang, Chaoren Wang +11
Recent advancements in speech generation models have been significantly driven by the use of large-scale training data. However, producing highly spontaneous, human-like speech rem…
Expressive paragraph text-to-speech synthesis with multi-step variational autoencoder
Xuyuan Li, Zengqiang Shang, Peiyang Shi +3
Neural networks have been able to generate high-quality single-sentence speech. However, it remains a challenge concerning audio-book speech synthesis due to the intra-paragraph co…
Sequential Topological Representations for Predictive Models of Deformable Objects
Rika Antonova, Anastasiia Varava, Peiyang Shi +2
Deformable objects present a formidable challenge for robotic manipulation due to the lack of canonical low-dimensional representations and the difficulty of capturing, predicting,…