8 papers
OmniVAE: An Audio-Video VAE with Cross-Modal Alignment for Joint Generation
Jun Zhan, Chen Yang, Yitian Gong +23
Recent generative models are moving beyond silent video or standalone audio synthesis toward the joint generation of synchronized audio and video. Despite this progress, jointly ge…
MOSS-VoiceGenerator: Create Realistic Voices with Natural Language Descriptions
Kexin Huang, Liwei Fan, Botian Jiang +11
Voice design from natural language aims to generate speaker timbres directly from free-form textual descriptions, allowing users to create voices tailored to specific roles, person…
MOSS-TTSD: Text to Spoken Dialogue Generation
Yuqian Zhang, Donghua Yu, Zhengyuan Lin +15
Spoken dialogue generation is crucial for applications like podcasts, dynamic commentary, and entertainment content, but poses significant challenges compared to single-utterance t…
MOSS-TTS Technical Report
Yitian Gong, Botian Jiang, Yiwei Zhao +23
This technical report presents MOSS-TTS, a speech generation foundation model built on a scalable recipe: discrete audio tokens, autoregressive modeling, and large-scale pretrainin…
Rethinking Multiple-Choice Questions for RLVR: Unlocking Potential via Distractor Design
Xu Guo, Qiming Ge, Jian Tong +8
Reinforcement Learning with Verifiable Rewards (RLVR) significantly enhances the reasoning capabilities of Large Language Models. When applied to RLVR, Multiple-Choice Questions (M…
MOSS-Audio-Tokenizer: Scaling Audio Tokenizers for Future Audio Foundation Models
Yitian Gong, Kuangwei Chen, Zhaoye Fei +9
Discrete audio tokenizers are fundamental to empowering large language models with native audio processing and generation capabilities. Despite recent progress, existing approaches…