1 citations · 2 across the 14 of their papers we have counts for
6 papers · 1 filter
How Should LLMs Listen While Speaking? A Study of User-Stream Routing in Full-Duplex Spoken Dialogue
Hui Lu, Xueyuan Chen, Huimeng Wang +4
Full-duplex spoken dialogue requires a model to keep listening while generating its own spoken response. This is challenging for large language models (LLMs), which are designed to…
Lamer-SSL: Layer-aware Mixture of LoRA Experts for Continual Multilingual Expansion of Self-supervised Models without Forgetting
Jing Xu, Minglin Wu, Xueyuan Chen +2
Despite their impressive performance, self-supervised speech models often struggle to generalize to new languages and tend to forget previously acquired knowledge during continual…
MiLorE-SSL: Scaling Multilingual Capabilities in Self-Supervised Models without Forgetting
Jing Xu, Minglin Wu, Xueyuan Chen +2
Self-supervised learning (SSL) has greatly advanced speech representation learning, but multilingual SSL models remain constrained to languages encountered during pretraining. Retr…
Speech Discrete Tokens or Continuous Features? A Comparative Analysis for Spoken Language Understanding in SpeechLLMs
Dingdong Wang, Junan Li, Mingyu Cui +3
With the rise of Speech Large Language Models (SpeechLLMs), two dominant approaches have emerged for speech processing: discrete tokens and continuous features. Each approach has d…
MMSU: A Massive Multi-task Spoken Language Understanding and Reasoning Benchmark
Dingdong Wang, Junan Li, Jincenzi Wu +4
Speech inherently contains rich acoustic information that extends far beyond the textual language. In real-world spoken language understanding, effective interpretation often requi…
A Comparative Study of Discrete Speech Tokens for Semantic-Related Tasks with Large Language Models
Dingdong Wang, Mingyu Cui, Dongchao Yang +2
With the rise of Speech Large Language Models (Speech LLMs), there has been growing interest in discrete speech tokens for their ability to integrate with text-based tokens seamles…