Marco-Voice Technical Report
Authors: name: Fengping Tian, name: Chenyang Lyu, name: Xuanfan Ni, name: Haoqin Sun, name: Qingjuan Li, name: Zhiqiang Qian, name: Haijun Li, name: Longyue Wang, name: Zhao Xu, name: Weihua Luo, name: Kaifu Zhang

This paper presents a multifunctional speech synthesis system that integrates
voice cloning and emotion control speech synthesis within a unified framework.
The goal of this work is to address longstanding challenges in achieving highly
expressive, controllable, and natural speech generation that faithfully
preserves speaker identity across diverse linguistic and emotional contexts.
Our approach introduces an effective speaker-emotion disentanglement mechanism
with in-batch contrastive learning, enabling independent manipulation of
speaker identity and eemotional style, as well as rotational emotional
embedding integration method for smooth emotion control. To support
comprehensive training and evaluation, we construct CSEMOTIONS, a high-quality
emotional speech dataset containing 10 hours of Mandarin speech from six
professional speakers across seven emotional categories. Extensive experiments
demonstrate that our system, Marco-Voice, achieves substantial improvements in
both objective and subjective metrics. Comprehensive evaluations and analysis
were conducted, results show that MarcoVoice delivers competitive performance
in terms of speech clarity and emotional richness, representing a substantial
advance in the field of expressive neural speech synthesis.