5 citations · 12 across the 12 of their papers we have counts for
6 papers · 1 filter
Multi-Level Knowledge Distillation for Speech Emotion Recognition in Noisy Conditions
Yang Liu, Haoqin Sun, Geng Chen +4
Speech emotion recognition (SER) performance deteriorates significantly in the presence of noise, making it challenging to achieve competitive performance in noisy conditions. To t…
TMS: A Temporal Multi-scale Backbone Design for Speaker Embedding
Ruiteng Zhang, Jianguo Wei, Xugang Lu +6
Speaker embedding is an important front-end module to explore discriminative speaker features for many speech applications where speaker information is needed. Current SOTA backbon…
MetricGAN+: An Improved Version of MetricGAN for Speech Enhancement
Szu-Wei Fu, Cheng Yu, Tsun-An Hsieh +4
The discrepancy between the cost function used for training a speech enhancement model and human auditory perception usually makes the quality of enhanced speech unsatisfactory. Ob…
Cross-scale Attention Model for Acoustic Event Classification
Xugang Lu, Peng Shen, Sheng Li +2
A major advantage of a deep convolutional neural network (CNN) is that the focused receptive field size is increased by stacking multiple convolutional layers. Accordingly, the mod…
Improving the Intelligibility of Electric and Acoustic Stimulation Speech Using Fully Convolutional Networks Based Speech Enhancement
Natalie Yu-Hsien Wang, Hsiao-Lan Sharon Wang, Tao-Wei Wang +4
The combined electric and acoustic stimulation (EAS) has demonstrated better speech recognition than conventional cochlear implant (CI) and yielded satisfactory performance under q…
Speech Dereverberation Based on Integrated Deep and Ensemble Learning Algorithm
Wei-Jen Lee, Syu-Siang Wang, Fei Chen +3
Reverberation, which is generally caused by sound reflections from walls, ceilings, and floors, can result in severe performance degradation of acoustic applications. Due to a comp…