24 citations · 32 across the 20 of their papers we have counts for
22 papers
WordVoice: Explicit and Decoupled Multi-Dimensional Word-Level Control for LLM-Based TTS
Sihang Nie, Jinxin Ji, Xiaofen Xing +4
While recent Large Language Model (LLM)-based Text-to-Speech (TTS) systems have achieved remarkable naturalness, they predominantly rely on implicit end-to-end generation paradigms…
HPRO: Hierarchical Progressive Reward Optimization via Preference Extraction for Emotional Text-to-Speech
Sihang Nie, Xiaofen Xing, Rui Xing +5
Recently, Large Language Model (LLM)-based Text-to-Speech (TTS) models have achieved remarkable naturalness. However, the standard Supervised Fine-Tuning paradigm often converges t…
PhysDrift: Bridging the Embodiment Gap in Humanoid Co-Speech Motion Generation
Zhangzhao Liang, Xiaofen Xing, Mingyue Yang +2
Humanoid robots require co-speech motions that are not only expressive and speech-aligned, but also physically executable under embodiment constraints. Existing co-speech generatio…
NVMOS: Non-Verbal Vocalization Quality Assessment in Speech
Jialong Mai, Jinxin Ji, Xiaofen Xing +2
Non-verbal vocalizations (NVs), such as laughter, sighs, and coughs, are important acoustic cues for emotion and intent. Existing speech quality assessment methods typically focus…
MAGIC-TTS: Fine-Grained Controllable Speech Synthesis with Explicit Local Duration and Pause Control
Jialong Mai, Xiaofen Xing, Xiangmin Xu
Fine-grained local timing control is still absent from modern text-to-speech systems: existing approaches typically provide only utterance-level duration or global speaking-rate co…
MimicParts: Part-aware Style Injection for Speech-Driven 3D Motion Generation
Lianlian Liu, YongKang He, Zhaojie Chu +2
Generating stylized 3D human motion from speech signals presents substantial challenges, primarily due to the intricate and fine-grained relationships among speech signals, individ…
BridgeCode: A Dual Speech Representation Paradigm for Autoregressive Zero-Shot Text-to-Speech Synthesis
Jingyuan Xing, Mingru Yang, Zhipeng Li +2
Autoregressive (AR) frameworks have recently achieved remarkable progress in zero-shot text-to-speech (TTS) by leveraging discrete speech tokens and large language model techniques…
CATCH: A Novel Data Synthesis Framework for High Therapy Fidelity and Memory-Driven Planning Chain of Thought in AI Counseling
Mingyu Chen, Jingkai Lin, Zhaojie Chu +3
Recently, advancements in AI counseling based on large language models have shown significant progress. However, existing studies employ a one-time generation approach to synthesiz…
MNV-17: A High-Quality Performative Mandarin Dataset for Nonverbal Vocalization Recognition in Speech
Jialong Mai, Jinxin Ji, Xiaofen Xing +4
Mainstream Automatic Speech Recognition (ASR) systems excel at transcribing lexical content, but largely fail to recognize nonverbal vocalizations (NVs) embedded in speech, such as…
HD-PPT: Hierarchical Decoding of Content- and Prompt-Preference Tokens for Instruction-based TTS
Sihang Nie, Xiaofen Xing, Jingyuan Xing +2
Large Language Model (LLM)-based Text-to-Speech (TTS) models have already reached a high degree of naturalness. However, the precision control of TTS inference is still challenging…
Parallel GPT: Harmonizing the Independence and Interdependence of Acoustic and Semantic Information for Zero-Shot Text-to-Speech
Jingyuan Xing, Zhipeng Li, Jialong Mai +2
Advances in speech representation and large language models have enhanced zero-shot text-to-speech (TTS) performance. However, existing zero-shot TTS models face challenges in capt…
Long-Context Speech Synthesis with Context-Aware Memory
Zhipeng Li, Xiaofen Xing, Jingyuan Xing +3
In long-text speech synthesis, current approaches typically convert text to speech at the sentence-level and concatenate the results to form pseudo-paragraph-level speech. These me…
From Flat to Round: Redefining Brain Decoding with Surface-Based fMRI and Cortex Structure
Sijin Yu, Zijiao Chen, Wenxuan Wu +6
Reconstructing visual stimuli from human brain activity (e.g., fMRI) bridges neuroscience and computer vision by decoding neural representations. However, existing methods often ov…
Dynamic Parameter Memory: Temporary LoRA-Enhanced LLM for Long-Sequence Emotion Recognition in Conversation
Jialong Mai, Xiaofen Xing, Yawei Li +4
Recent research has focused on applying speech large language model (SLLM) to improve speech emotion recognition (SER). However, the inherently high frame rate in speech modality s…
S2SBench: A Benchmark for Quantifying Intelligence Degradation in Speech-to-Speech Large Language Models
Yuanbo Fang, Haoze Sun, Jun Liu +5
End-to-end speech large language models ((LLMs)) extend the capabilities of text-based models to directly process and generate audio tokens. However, this often leads to a decline…
PsyDT: Using LLMs to Construct the Digital Twin of Psychological Counselor with Personalized Counseling Style for Psychological Counseling
Haojie Xie, Yirong Chen, Xiaofen Xing +2
Currently, large language models (LLMs) have made significant progress in the field of psychological counseling. However, existing mental health LLMs overlook a critical issue wher…
SleepCoT: A Lightweight Personalized Sleep Health Model via Chain-of-Thought Distillation
Huimin Zheng, Xiaofeng Xing, Xiangmin Xu
We present a novel approach to personalized sleep health management using few-shot Chain-of-Thought (CoT) distillation, enabling small-scale language models (> 2B parameters) to ri…
AS-Speech: Adaptive Style For Speech Synthesis
Zhipeng Li, Xiaofen Xing, Jun Wang +4
In recent years, there has been significant progress in Text-to-Speech (TTS) synthesis technology, enabling the high-quality synthesis of voices in common scenarios. In unseen situ…
Towards Zero-shot Human-Object Interaction Detection via Vision-Language Integration
Weiying Xue, Qi Liu, Qiwei Xiong +4
Human-object interaction (HOI) detection aims to locate human-object pairs and identify their interaction categories in images. Most existing methods primarily focus on supervised…
PointCore: Efficient Unsupervised Point Cloud Anomaly Detector Using Local-Global Features
Baozhu Zhao, Qiwei Xiong, Xiaohan Zhang +4
Three-dimensional point cloud anomaly detection that aims to detect anomaly data points from a training set serves as the foundation for a variety of applications, including indust…
SoulChat: Improving LLMs' Empathy, Listening, and Comfort Abilities through Fine-tuning with Multi-turn Empathy Conversations
Yirong Chen, Xiaofen Xing, Jingkai Lin +4
Large language models (LLMs) have been widely applied in various fields due to their excellent capability for memorizing knowledge and chain of thought (CoT). When these language m…
BianQue: Balancing the Questioning and Suggestion Ability of Health LLMs with Multi-turn Health Conversations Polished by ChatGPT
Yirong Chen, Zhenyu Wang, Xiaofen Xing +8
Large language models (LLMs) have performed well in providing general and extensive health suggestions in single-turn conversations, exemplified by systems such as ChatGPT, ChatGLM…