1 citations · 1 across the 5 of their papers we have counts for
7 papers
A Unified Spoken Language Model with Injected Emotional-Attribution Thinking for Human-like Interaction
Qing Wang, Zehan Li, Yaodong Song +6
This paper presents a unified spoken language model for emotional intelligence, enhanced by a novel data construction strategy termed Injected Emotional-Attribution Thinking (IEAT)…
Multilingual Speech Recognition Using Discrete Tokens with a Two-step Training Strategy
Zehan Li, Yan Yang, Xueqing Li +3
Pre-trained models, especially self-supervised learning (SSL) models, have demonstrated impressive results in automatic speech recognition (ASR) task. While most applications of SS…
GOAT-SLM: A Spoken Language Model with Paralinguistic and Speaker Characteristic Awareness
Hongjie Chen, Zehan Li, Yaodong Song +13
Recent advances in end-to-end spoken language models (SLMs) have significantly improved the ability of AI systems to engage in natural spoken interactions. However, most existing m…
DIFFA: Large Language Diffusion Models Can Listen and Understand
Jiaming Zhou, Hongjie Chen, Shiwan Zhao +9
Recent advances in large language models (LLMs) have shown remarkable capabilities across textual and multimodal domains. In parallel, diffusion-based language models have emerged…
Leveraging LLM and Self-Supervised Training Models for Speech Recognition in Chinese Dialects: A Comparative Analysis
Tianyi Xu, Hongjie Chen, Wang Qing +6
Large-scale training corpora have significantly improved the performance of ASR models. Unfortunately, due to the relative scarcity of data, Chinese accents and dialects remain a c…
GOAT-TTS: Expressive and Realistic Speech Generation via A Dual-Branch LLM
Yaodong Song, Hongjie Chen, Jie Lian +8
While large language models (LLMs) have revolutionized text-to-speech (TTS) synthesis through discrete tokenization paradigms, current architectures exhibit fundamental tensions be…