13 citations · 13 across the 7 of their papers we have counts for
8 papers
An Exploration of Mamba for Speech Self-Supervised Models
Tzu-Quan Lin, Heng-Cheng Kuo, Tzu-Chieh Wei +5
While Mamba has demonstrated strong performance in language modeling, its potential as a speech self-supervised learning (SSL) model remains underexplored, with prior studies limit…
Detecting the Undetectable: Assessing the Efficacy of Current Spoof Detection Methods Against Seamless Speech Edits
Sung-Feng Huang, Heng-Cheng Kuo, Zhehuai Chen +6
Neural speech editing advancements have raised concerns about their misuse in spoofing attacks. Traditional partially edited speech corpora primarily focus on cut-and-paste edits,…
Scalable Ensemble-based Detection Method against Adversarial Attacks for speaker verification
Haibin Wu, Heng-Cheng Kuo, Yu Tsao +1
Automatic speaker verification (ASV) is highly susceptible to adversarial attacks. Purification modules are usually adopted as a pre-processing to mitigate adversarial noise. Howev…
Study on the Correlation between Objective Evaluations and Subjective Speech Quality and Intelligibility
Hsin-Tien Chiang, Kuo-Hsuan Hung, Szu-Wei Fu +3
Subjective tests are the gold standard for evaluating speech quality and intelligibility; however, they are time-consuming and expensive. Thus, objective measures that align with h…
Partially Fake Audio Detection by Self-attention-based Fake Span Discovery
Haibin Wu, Heng-Cheng Kuo, Naijun Zheng +5
The past few years have witnessed the significant advances of speech synthesis and voice conversion technologies. However, such technologies can undermine the robustness of broadly…
Toward Real-World Voice Disorder Classification
Heng-Cheng Kuo, Yu-Peng Hsieh, Huan-Hsin Tseng +3
Objective: Voice disorders significantly compromise individuals' ability to speak in their daily lives. Without early diagnosis and treatment, these disorders may deteriorate drast…
Domain-adaptive Fall Detection Using Deep Adversarial Training
Kai-Chun Liu, Michael Can, Heng-Cheng Kuo +4
Fall detection (FD) systems are important assistive technologies for healthcare that can detect emergency fall events and alert caregivers. However, it is not easy to obtain large-…
Boosting Objective Scores of a Speech Enhancement Model by MetricGAN Post-processing
Szu-Wei Fu, Chien-Feng Liao, Tsun-An Hsieh +9
The Transformer architecture has demonstrated a superior ability compared to recurrent neural networks in many different natural language processing applications. Therefore, our st…