Xunying Liu

Recurrent Neural Network Language Model Training Using Natural Gradient

2019

Recurrent neural network language models (RNNLMs) have become an increasing popular choice for state-of-the-art speech recognition systems. RNNLMs are normally trained by minimizing the cross entropy (CE) using the stochastic gradient descent (SGD) algorithm. However, …

Improved End-to-End Dysarthric Speech Recognition via Meta-learning Based Model Re-initialization

2021

Dysarthric speech recognition is a challenging task as dysarthric data is limited and its acoustics deviate significantly from normal speech. Model-based speaker adaptation is a promising method by using the limited dysarthric speech to fine-tune …

Channel-wise Gated Res2Net: Towards Robust Detection of Synthetic Speech Attacks

2021 · arXiv (Cornell University)

Existing approaches for anti-spoofing in automatic speaker verification (ASV) still lack generalizability to unseen attacks. The Res2Net approach designs a residual-like connection between feature groups within one block, which increases the possible receptive fields and …