most citedHAM-TTS: Hierarchical Acoustic Modeling for Token-Based Zero-Shot Text-to-Speech with Model and Data Scaling

1 citations · 1 across the 4 of their papers we have counts for

collaborators

5 papers

eess.AS2026

MSVAE: Rethinking Musical Semantics in Continuous Latent Spaces

Guobin Ma, Yuepeng Jiang, Dake Guo +15

Continuous latent representations underlie recent diffusion-based lyrics-to-song and text-to-music systems, yet aligning lyric conditions with these latents remains difficult: exis…

eess.AS2026

Rethinking Music Tokenization: A Semantic Codec toward High-Fidelity LLM Music Generation

Huakang Chen, Guobin Ma, Yuepeng Jiang +10

Discrete audio tokenization has become the critical interface between raw waveforms and autoregressive modeling in recent music generation. As a result, music tokenizers must simul…

eess.AS2026

SoulX-Singer: Towards High-Quality Zero-Shot Singing Voice Synthesis

Jiale Qian, Hao Meng, Tian Zheng +17

While recent years have witnessed rapid progress in speech synthesis, open-source singing voice synthesis (SVS) systems still face significant barriers to industrial deployment, pa…

eess.AS2024

InstructSing: High-Fidelity Singing Voice Generation via Instructing Yourself

Chang Zeng, Chunhui Wang, Xiaoxiao Miao +3

It is challenging to accelerate the training process while ensuring both high-quality generated voices and acceptable inference speed. In this paper, we propose a novel neural voco…

cs.SD2024★ 1 cited

HAM-TTS: Hierarchical Acoustic Modeling for Token-Based Zero-Shot Text-to-Speech with Model and Data Scaling

Chunhui Wang, Chang Zeng, Bowen Zhang +6

Token-based text-to-speech (TTS) models have emerged as a promising avenue for generating natural and realistic speech, yet they grapple with low pronunciation accuracy, speaking s…