6 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-Audio Technical Report
Chen Yang, Chufan Yu, Hanfu Chen +27
MOSS-Audio is a unified audio-language model for speech, environmental sound, and music understanding, supporting audio captioning, time-aware question answering, timestamped trans…
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…
VStyle: A Benchmark for Voice Style Adaptation with Spoken Instructions
Jun Zhan, Mingyang Han, Yuxuan Xie +11
Spoken language models (SLMs) have emerged as a unified paradigm for speech understanding and generation, enabling natural human machine interaction. However, while most progress h…
AnyGPT: Unified Multimodal LLM with Discrete Sequence Modeling
Jun Zhan, Junqi Dai, Jiasheng Ye +13
We introduce AnyGPT, an any-to-any multimodal language model that utilizes discrete representations for the unified processing of various modalities, including speech, text, images…
Data Mixing Laws: Optimizing Data Mixtures by Predicting Language Modeling Performance
Jiasheng Ye, Peiju Liu, Tianxiang Sun +3
Pretraining data of large language models composes multiple domains (e.g., web texts, academic papers, codes), whose mixture proportions crucially impact the competence of outcome…