8 citations · 15 across the 8 of their papers we have counts for
8 papers
Out-of-Distribution Detection Based on Total Variation Estimation
Dabiao Ma, Zhiba Su, Jian Yang +1
This paper introduces a novel approach to securing machine learning model deployments against potential distribution shifts in practical applications, the Total Variation Out-of-Di…
AccentBox: Towards High-Fidelity Zero-Shot Accent Generation
Jinzuomu Zhong, Korin Richmond, Zhiba Su +1
While recent Zero-Shot Text-to-Speech (ZS-TTS) models have achieved high naturalness and speaker similarity, they fall short in accent fidelity and control. To address this issue,…
Multi-Modal Automatic Prosody Annotation with Contrastive Pretraining of SSWP
Jinzuomu Zhong, Yang Li, Hui Huang +6
In expressive and controllable Text-to-Speech (TTS), explicit prosodic features significantly improve the naturalness and controllability of synthesised speech. However, manual pro…
TranssionADD: A multi-frame reinforcement based sequence tagging model for audio deepfake detection
Jie Liu, Zhiba Su, Hui Huang +5
Thanks to recent advancements in end-to-end speech modeling technology, it has become increasingly feasible to imitate and clone a user`s voice. This leads to a significant challen…
Improving Cross-lingual Speech Synthesis with Triplet Training Scheme
Jianhao Ye, Hongbin Zhou, Zhiba Su +4
Recent advances in cross-lingual text-to-speech (TTS) made it possible to synthesize speech in a language foreign to a monolingual speaker. However, there is still a large gap betw…
MHTTS: Fast multi-head text-to-speech for spontaneous speech with imperfect transcription
Dabiao Ma, Yitong Zhang, Meng Li +1
Neural network based end-to-end Text-to-Speech (TTS) has greatly improved the quality of synthesized speech. While how to use massive spontaneous speech without transcription effic…
FPETS : Fully Parallel End-to-End Text-to-Speech System
Dabiao Ma, Zhiba Su, Wenxuan Wang +1
End-to-end Text-to-speech (TTS) system can greatly improve the quality of synthesised speech. But it usually suffers form high time latency due to its auto-regressive structure. An…
UFANS: U-shaped Fully-Parallel Acoustic Neural Structure For Statistical Parametric Speech Synthesis With 20X Faster
Dabiao Ma, Zhiba Su, Yuhao Lu +2
Neural networks with Auto-regressive structures, such as Recurrent Neural Networks (RNNs), have become the most appealing structures for acoustic modeling of parametric text to spe…