10 citations · 22 across the 13 of their papers we have counts for
14 papers
SLM-TTA: A Framework for Test-Time Adaptation of Generative Spoken Language Models
Yuan-Kuei Wu, Yang Liu, Yiteng Huang +9
Spoken Language Models (SLMs) are increasingly central to modern speech-driven applications, but performance degrades under acoustic shift - real-world noise, reverberation, and mi…
Restore-R1: Efficient Image Restoration Agents via Reinforcement Learning with Multimodal LLM Perceptual Feedback
Jianglin Lu, Yuanwei Wu, Ziyi Zhao +4
Complex image restoration aims to recover high-quality images from inputs affected by multiple degradations such as blur, noise, rain, and compression artifacts. Recent restoration…
DeSTA2.5-Audio: Toward General-Purpose Large Audio Language Model with Self-Generated Cross-Modal Alignment
Ke-Han Lu, Zhehuai Chen, Szu-Wei Fu +25
We introduce DeSTA2.5-Audio, a general-purpose Large Audio Language Model (LALM) designed for robust auditory perception and instruction-following. Recent LALMs augment Large Langu…
A Novel Deep Learning Framework for Efficient Multichannel Acoustic Feedback Control
Yuan-Kuei Wu, Juan Azcarreta, Kashyap Patel +4
This study presents a deep-learning framework for controlling multichannel acoustic feedback in audio devices. Traditional digital signal processing methods struggle with convergen…
Codec-SUPERB @ SLT 2024: A lightweight benchmark for neural audio codec models
Haibin Wu, Xuanjun Chen, Yi-Cheng Lin +13
Neural audio codec models are becoming increasingly important as they serve as tokenizers for audio, enabling efficient transmission or facilitating speech language modeling. The i…
SpeechPrompt: Prompting Speech Language Models for Speech Processing Tasks
Kai-Wei Chang, Haibin Wu, Yu-Kai Wang +6
Prompting has become a practical method for utilizing pre-trained language models (LMs). This approach offers several advantages. It allows an LM to adapt to new tasks with minimal…