9 citations · 13 across the 11 of their papers we have counts for
11 papers
Toward Improving Synthetic Audio Spoofing Detection Robustness via Meta-Learning and Disentangled Training With Adversarial Examples
Zhenyu Wang, John H. L. Hansen
Advances in automatic speaker verification (ASV) promote research into the formulation of spoofing detection systems for real-world applications. The performance of ASV systems can…
Efficient Adapter Tuning of Pre-trained Speech Models for Automatic Speaker Verification
Mufan Sang, John H. L. Hansen
With excellent generalization ability, self-supervised speech models have shown impressive performance on various downstream speech tasks in the pre-training and fine-tuning paradi…
Multi-objective Non-intrusive Hearing-aid Speech Assessment Model
Hsin-Tien Chiang, Szu-Wei Fu, Hsin-Min Wang +2
Without the need for a clean reference, non-intrusive speech assessment methods have caught great attention for objective evaluations. While deep learning models have been used to…
Advanced accent/dialect identification and accentedness assessment with multi-embedding models and automatic speech recognition
Shahram Ghorbani, John H. L. Hansen
Accurately classifying accents and assessing accentedness in non-native speakers are both challenging tasks due to the complexity and diversity of accent and dialect variations. In…
What Can an Accent Identifier Learn? Probing Phonetic and Prosodic Information in a Wav2vec2-based Accent Identification Model
Mu Yang, Ram C. M. C. Shekar, Okim Kang +1
This study is focused on understanding and quantifying the change in phoneme and prosody information encoded in the Self-Supervised Learning (SSL) model, brought by an accent ident…
Improving Transformer-based Networks With Locality For Automatic Speaker Verification
Mufan Sang, Yong Zhao, Gang Liu +2
Recently, Transformer-based architectures have been explored for speaker embedding extraction. Although the Transformer employs the self-attention mechanism to efficiently model th…