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eess.AS2024

CSSinger: End-to-End Chunkwise Streaming Singing Voice Synthesis System Based on Conditional Variational Autoencoder

Jianwei Cui, Yu Gu, Shihao Chen +3

Singing Voice Synthesis (SVS) aims to generate singing voices of high fidelity and expressiveness. Conventional SVS systems usually utilize an acoustic model to transform a music s…

eess.AS2024

DurIAN-E 2: Duration Informed Attention Network with Adaptive Variational Autoencoder and Adversarial Learning for Expressive Text-to-Speech Synthesis

Yu Gu, Qiushi Zhu, Guangzhi Lei +2

This paper proposes an improved version of DurIAN-E (DurIAN-E 2), which is also a duration informed attention neural network for expressive and high-fidelity text-to-speech (TTS) s…

eess.AS2024

SiFiSinger: A High-Fidelity End-to-End Singing Voice Synthesizer based on Source-filter Model

Jianwei Cui, Yu Gu, Chao Weng +3

This paper presents an advanced end-to-end singing voice synthesis (SVS) system based on the source-filter mechanism that directly translates lyrical and melodic cues into expressi…

eess.AS2024

LCM-SVC: Latent Diffusion Model Based Singing Voice Conversion with Inference Acceleration via Latent Consistency Distillation

Shihao Chen, Yu Gu, Jianwei Cui +3

Any-to-any singing voice conversion (SVC) aims to transfer a target singer's timbre to other songs using a short voice sample. However many diffusion model based any-to-any SVC met…

eess.AS2024

LDM-SVC: Latent Diffusion Model Based Zero-Shot Any-to-Any Singing Voice Conversion with Singer Guidance

Shihao Chen, Yu Gu, Jie Zhang +4

Any-to-any singing voice conversion (SVC) is an interesting audio editing technique, aiming to convert the singing voice of one singer into that of another, given only a few second…