49 citations · 158 across the 25 of their papers we have counts for
7 papers · 1 filter
FusionFormer: Fusing Operations in Transformer for Efficient Streaming Speech Recognition
Xingchen Song, Di Wu, Binbin Zhang +8
The recently proposed Conformer architecture which combines convolution with attention to capture both local and global dependencies has become the \textit{de facto} backbone model…
A Multimodal Machine Learning Framework for Teacher Vocal Delivery Evaluation
Hang Li, Yu Kang, Yang Hao +3
The quality of vocal delivery is one of the key indicators for evaluating teacher enthusiasm, which has been widely accepted to be connected to the overall course qualities. Howeve…
Multi-Scale Attention Neural Network for Acoustic Echo Cancellation
Lu Ma, Song Yang, Yaguang Gong +1
Acoustic Echo Cancellation (AEC) plays a key role in speech interaction by suppressing the echo received at microphone introduced by acoustic reverberations from loudspeakers. Sinc…
Noise Classification Aided Attention-Based Neural Network for Monaural Speech Enhancement
Lu Ma, Song Yang, Yaguang Gong +1
This paper proposes an noise type classification aided attention-based neural network approach for monaural speech enhancement. The network is constructed based on a previous work…
Multi-Scale Temporal Convolution Network for Classroom Voice Detection
Lu Ma, Xintian Wang, Song Yang +2
Teaching with the cooperation of expert teacher and assistant teacher, which is the so-called "double-teachers classroom", i.e., the course is giving by the expert online and prese…
EchoFilter: End-to-End Neural Network for Acoustic Echo Cancellation
Lu Ma, Song Yang, Yaguang Gong +2
Acoustic Echo Cancellation (AEC) whose aim is to suppress the echo originated from acoustic coupling between loudspeakers and microphones, plays a key role in voice interaction. Li…
Learning Fine-Grained Cross Modality Excitement for Speech Emotion Recognition
Hang Li, Wenbiao Ding, Zhongqin Wu +1
Speech emotion recognition is a challenging task because the emotion expression is complex, multimodal and fine-grained. In this paper, we propose a novel multimodal deep learning…