4 papers
UniTTS: An end-to-end TTS system without decoupling of acoustic and semantic information
Rui Wang, Qianguo Sun, Tianrong Chen +3
The emergence of multi-codebook neutral audio codecs such as Residual Vector Quantization (RVQ) and Group Vector Quantization (GVQ) has significantly advanced Large-Language-Model…
MADial-Bench: Towards Real-world Evaluation of Memory-Augmented Dialogue Generation
Junqing He, Liang Zhu, Rui Wang +3
Long-term memory is important for chatbots and dialogue systems (DS) to create consistent and human-like conversations, evidenced by numerous developed memory-augmented DS (MADS).…
CAPE: A Chinese Dataset for Appraisal-based Emotional Generation using Large Language Models
June M. Liu, He Cao, Renliang Sun +3
Generating emotionally appropriate responses in conversations with large language models presents a significant challenge due to the complexities of human emotions and cognitive pr…
Fostering Natural Conversation in Large Language Models with NICO: a Natural Interactive COnversation dataset
Renliang Sun, Mengyuan Liu, Shiping Yang +3
Benefiting from diverse instruction datasets, contemporary Large Language Models (LLMs) perform effectively as AI assistants in collaborating with humans. However, LLMs still strug…