6 papers
Recent Advances in Large Langauge Model Benchmarks against Data Contamination: From Static to Dynamic Evaluation
Simin Chen, Yiming Chen, Zexin Li +8
Data contamination has received increasing attention in the era of large language models (LLMs) due to their reliance on vast Internet-derived training corpora. To mitigate the ris…
UniCodec: Unified Audio Codec with Single Domain-Adaptive Codebook
Yidi Jiang, Qian Chen, Shengpeng Ji +6
The emergence of audio language models is empowered by neural audio codecs, which establish critical mappings between continuous waveforms and discrete tokens compatible with langu…
VoiceBench: Benchmarking LLM-Based Voice Assistants
Yiming Chen, Xianghu Yue, Chen Zhang +3
Building on the success of large language models (LLMs), recent advancements such as GPT-4o have enabled real-time speech interactions through LLM-based voice assistants, offering…
Transferable Adversarial Attacks against ASR
Xiaoxue Gao, Zexin Li, Yiming Chen +2
Given the extensive research and real-world applications of automatic speech recognition (ASR), ensuring the robustness of ASR models against minor input perturbations becomes a cr…
Beyond Single-Audio: Advancing Multi-Audio Processing in Audio Large Language Models
Yiming Chen, Xianghu Yue, Xiaoxue Gao +4
Various audio-LLMs (ALLMs) have been explored recently for tackling different audio tasks simultaneously using a single, unified model. While existing evaluations of ALLMs primaril…
Text-guided HuBERT: Self-Supervised Speech Pre-training via Generative Adversarial Networks
Duo Ma, Xianghu Yue, Junyi Ao +2
Human language can be expressed in either written or spoken form, i.e. text or speech. Humans can acquire knowledge from text to improve speaking and listening. However, the quest…