Marco-Voice Technical Report
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.
6892d2e88da45ffb0a2b24cf
Fengping Tian
6892d2e88da45ffb0a2b24d0
Chenyang Lyu
6892d2e88da45ffb0a2b24d1
Xuanfan Ni
claimed_verified
2025-08-08T16:22:54.088Z
67bb37bdc4d637c75d917690
https://cdn-avatars.huggingface.co/v1/production/uploads/no-auth/PJ_0apRpSEsWrFpd1CKol.png
Ni
user
Patrick828
6892d2e88da45ffb0a2b24d2
Haoqin Sun
6892d2e88da45ffb0a2b24d3
Qingjuan Li
6892d2e88da45ffb0a2b24d4
Zhiqiang Qian
6892d2e88da45ffb0a2b24d5
Haijun Li
6892d2e88da45ffb0a2b24d6
Longyue Wang
6892d2e88da45ffb0a2b24d7
Zhao Xu
6892d2e88da45ffb0a2b24d8
Weihua Luo
6892d2e88da45ffb0a2b24d9
Kaifu Zhang
Marco-Voice Technical Report
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.
A multifunctional speech synthesis system integrates voice cloning and emotion control using speaker-emotion disentanglement and rotational emotional embeddings, achieving high expressive and natural speech.
voice cloning emotion control speaker-emotion disentanglement in-batch contrastive learning rotational emotional embedding emotional speech dataset Marco-Voice expressive neural speech synthesis