1 citations · 1 across the 10 of their papers we have counts for
10 papers
Rethinking Length-Based Training: Batch Composition and Loss Normalization in Speech Token Language Models
Hongjin Song, Runwu Shi, Weiqiao Shan +4
Short-to-long training is a simple curriculum for speech models, but its gains can be difficult to interpret. In speech token language models, length-based training can change the…
Robust Speech Emotion Recognition under Tone-Word Conflict: A Benchmark and Framework
Xiaojiang Peng, Dawei Huang, Yongjie Lv +5
Speech emotion recognition (SER) is a crucial component of human-computer interaction, attracting extensive attention from both industry and academia. However, existing SER systems…
Joint Residual Reweighting for Classifier Free Guidance in Flow-Matching Zero-Shot TTS
Runwu Shi, Yujin Wang, Hongjin Song +8
Classifier-free guidance (CFG) is widely used in flow-matching-based zero-shot text-to-speech (TTS), where generation is conditioned on text content and a speech prompt. Standard C…
SPRI: SVD-Partitioned Residual Initialization for Data-Constrained MoE Upcycling
Weiqiao Shan, Ruixiang Mao, Yuang Li +10
Mixture-of-Experts (MoE) models enable efficient scaling, but training them from scratch remains prohibitively expensive. MoE upcycling mitigates this cost by converting pretrained…
VividVoice: A Unified Framework for Scene-Aware Visually-Driven Speech Synthesis
Chengyuan Ma, Jiawei Jin, Ruijie Xiong +3
We introduce and define a novel task-Scene-Aware Visually-Driven Speech Synthesis, aimed at addressing the limitations of existing speech generation models in creating immersive au…
When Tone and Words Disagree: Towards Robust Speech Emotion Recognition under Acoustic-Semantic Conflict
Dawei Huang, Yongjie Lv, Ruijie Xiong +2
Speech Emotion Recognition (SER) systems often assume congruence between vocal emotion and lexical semantics. However, in real-world interactions, acoustic-semantic conflict is com…
ReStyle-TTS: Relative and Continuous Style Control for Zero-Shot Speech Synthesis
Haitao Li, Chunxiang Jin, Chenglin Li +3
Zero-shot text-to-speech models can clone a speaker's timbre from a short reference audio, but they also strongly inherit the speaking style present in the reference. As a result,…
Ming-UniAudio: Speech LLM for Joint Understanding, Generation and Editing with Unified Representation
Canxiang Yan, Chunxiang Jin, Dawei Huang +22
Existing speech models suffer from competing requirements on token representations by understanding and generation tasks. This discrepancy in representation prevents speech languag…
Ming-Flash-Omni: A Sparse, Unified Architecture for Multimodal Perception and Generation
Inclusion AI, :, Bowen Ma +73
We propose Ming-Flash-Omni, an upgraded version of Ming-Omni, built upon a sparser Mixture-of-Experts (MoE) variant of Ling-Flash-2.0 with 100 billion total parameters, of which on…
Ming-Omni: A Unified Multimodal Model for Perception and Generation
Inclusion AI, Biao Gong, Cheng Zou +55
We propose Ming-Omni, a unified multimodal model capable of processing images, text, audio, and video, while demonstrating strong proficiency in both speech and image generation. M…