2 citations · 6 across the 31 of their papers we have counts for
15 papers · 1 filter
Sequential Trajectories and Simultaneous Blending: Multi-Emotion Modeling for Instruction-Following TTS
Yan Zhou, Yun Hong, Yang Feng
Natural-language instructions enable flexible control of synthesized speech, yet emotional TTS systems primarily model a single utterance-level affect, leaving multi-emotion contro…
BayLing-Duplex: Native Full-Duplex Speech Dialogue with a Single Autoregressive LLM
Qingkai Fang, Shoutao Guo, Yang Feng
Real-time, full-duplex speech interaction is a key feature of next-generation spoken chatbots, allowing the model to listen and speak at the same time and to handle natural phenome…
FreezeEmpath: Efficient Training for Empathetic Spoken Chatbots with Frozen LLMs
Yun Hong, Yan Zhou, Yang Feng
Empathy is essential for fostering natural interactions in spoken dialogue systems, as it enables machines to recognize the emotional tone of human speech and deliver empathetic re…
Language on Demand, Knowledge at Core: Composing LLMs with Encoder-Decoder Translation Models for Extensible Multilinguality
Mengyu Bu, Yang Feng
Large language models (LLMs) exhibit strong general intelligence, yet their multilingual performance remains highly imbalanced. Although LLMs encode substantial cross-lingual knowl…
SpecBound: Adaptive Bounded Self-Speculation with Layer-wise Confidence Calibration
Zhuofan Wen, Yang Feng
Speculative decoding has emerged as a promising approach to accelerate autoregressive inference in large language models (LLMs). Self-draft methods, which leverage the base LLM its…
Efficient Training for Cross-lingual Speech Language Models
Yan Zhou, Qingkai Fang, Yun Hong +1
Currently, large language models (LLMs) predominantly focus on the text modality. To enable more natural human-AI interaction, speech LLMs are emerging, but building effective end-…