most citedImproving Speech Enhancement Performance by Leveraging Contextual Broad Phonetic Class Information

3 citations · 4 across the 4 of their papers we have counts for

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eess.AS2023

Multi-Task Pseudo-Label Learning for Non-Intrusive Speech Quality Assessment Model

Ryandhimas E. Zezario, Bo-Ren Brian Bai, Chiou-Shann Fuh +2

This study proposes a multi-task pseudo-label learning (MPL)-based non-intrusive speech quality assessment model called MTQ-Net. MPL consists of two stages: obtaining pseudo-label…

eess.AS2023★ 1 cited

Leveraging Self-Supervised Audio-Visual Pretrained Models to Improve Vocoded Speech Intelligibility in Cochlear Implant Simulation

Richard Lee Lai, Jen-Cheng Hou, I-Chun Chern +6

Individuals with hearing impairments face challenges in their ability to comprehend speech, particularly in noisy environments. The aim of this study is to explore the effectivenes…