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20202025
most citedBoosting Objective Scores of a Speech Enhancement Model by MetricGAN Post-processing

13 citations · 13 across the 7 of their papers we have counts for

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5 papers · 1 filter

eess.AS2023

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…

eess.AS2023

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…

eess.AS2022

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…

eess.AS2021

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…

eess.AS2020★ 13 cited

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…