3 citations · 7 across the 12 of their papers we have counts for
12 papers
AuK Technical Report: An Open-Source Foundational Model for Speech Generation and Editing
Ziyang Ma, Zhikang Niu, Wenming Tu +30
We introduce AuK, an open-source foundational model that unifies speech generation and editing through a common interface of natural-language instructions and audio context. To sup…
FleSpeech: Flexibly Controllable Speech Generation with Various Prompts
Hanzhao Li, Yuke Li, Xinsheng Wang +4
Controllable speech generation methods typically rely on single or fixed prompts, hindering creativity and flexibility. These limitations make it difficult to meet specific user ne…
MSM-VC: High-fidelity Source Style Transfer for Non-Parallel Voice Conversion by Multi-scale Style Modeling
Zhichao Wang, Xinsheng Wang, Qicong Xie +4
In addition to conveying the linguistic content from source speech to converted speech, maintaining the speaking style of source speech also plays an important role in the voice co…
UniSyn: An End-to-End Unified Model for Text-to-Speech and Singing Voice Synthesis
Yi Lei, Shan Yang, Xinsheng Wang +4
Text-to-speech (TTS) and singing voice synthesis (SVS) aim at generating high-quality speaking and singing voice according to textual input and music scores, respectively. Unifying…
Expressive-VC: Highly Expressive Voice Conversion with Attention Fusion of Bottleneck and Perturbation Features
Ziqian Ning, Qicong Xie, Pengcheng Zhu +5
Voice conversion for highly expressive speech is challenging. Current approaches struggle with the balancing between speaker similarity, intelligibility and expressiveness. To addr…
Cross-speaker Emotion Transfer Based On Prosody Compensation for End-to-End Speech Synthesis
Tao Li, Xinsheng Wang, Qicong Xie +3
Cross-speaker emotion transfer speech synthesis aims to synthesize emotional speech for a target speaker by transferring the emotion from reference speech recorded by another (sour…
End-to-End Voice Conversion with Information Perturbation
Qicong Xie, Shan Yang, Yi Lei +2
The ideal goal of voice conversion is to convert the source speaker's speech to sound naturally like the target speaker while maintaining the linguistic content and the prosody of…
Multi-speaker Multi-style Text-to-speech Synthesis With Single-speaker Single-style Training Data Scenarios
Qicong Xie, Tao Li, Xinsheng Wang +4
In the existing cross-speaker style transfer task, a source speaker with multi-style recordings is necessary to provide the style for a target speaker. However, it is hard for one…
One-shot Voice Conversion For Style Transfer Based On Speaker Adaptation
Zhichao Wang, Qicong Xie, Tao Li +4
One-shot style transfer is a challenging task, since training on one utterance makes model extremely easy to over-fit to training data and causes low speaker similarity and lack of…
Cross-speaker emotion disentangling and transfer for end-to-end speech synthesis
Tao Li, Xinsheng Wang, Qicong Xie +2
The cross-speaker emotion transfer task in text-to-speech (TTS) synthesis particularly aims to synthesize speech for a target speaker with the emotion transferred from reference sp…
AnyoneNet: Synchronized Speech and Talking Head Generation for Arbitrary Person
Xinsheng Wang, Qicong Xie, Jihua Zhu +2
Automatically generating videos in which synthesized speech is synchronized with lip movements in a talking head has great potential in many human-computer interaction scenarios. I…
The Multi-speaker Multi-style Voice Cloning Challenge 2021
Qicong Xie, Xiaohai Tian, Guanghou Liu +9
The Multi-speaker Multi-style Voice Cloning Challenge (M2VoC) aims to provide a common sizable dataset as well as a fair testbed for the benchmarking of the popular voice cloning t…