10 citations · 26 across the 14 of their papers we have counts for
7 papers · 1 filter
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…
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…
Improving the transferability of speech separation by meta-learning
Kuan-Po Huang, Yuan-Kuei Wu, Hung-yi Lee
Speech separation aims to separate multiple speech sources from a speech mixture. Although speech separation is well-solved on some existing English speech separation benchmarks, i…
Multi-accent Speech Separation with One Shot Learning
Kuan-Po Huang, Yuan-Kuei Wu, Hung-yi Lee
Speech separation is a problem in the field of speech processing that has been studied in full swing recently. However, there has not been much work studying a multi-accent speech…
One Shot Learning for Speech Separation
Yuan-Kuei Wu, Kuan-Po Huang, Yu Tsao +1
Despite the recent success of speech separation models, they fail to separate sources properly while facing different sets of people or noisy environments. To tackle this problem,…
SADDEL: Joint Speech Separation and Denoising Model based on Multitask Learning
Yuan-Kuei Wu, Chao-I Tuan, Hung-yi Lee +1
Speech data collected in real-world scenarios often encounters two issues. First, multiple sources may exist simultaneously, and the number of sources may vary with time. Second, t…
MITAS: A Compressed Time-Domain Audio Separation Network with Parameter Sharing
Chao-I Tuan, Yuan-Kuei Wu, Hung-yi Lee +1
Deep learning methods have brought substantial advancements in speech separation (SS). Nevertheless, it remains challenging to deploy deep-learning-based models on edge devices. Th…