5 citations · 10 across the 9 of their papers we have counts for
10 papers
Topic Classification on Spoken Documents Using Deep Acoustic and Linguistic Features
Tan Liu, Wu Guo, Bin Gu
Topic classification systems on spoken documents usually consist of two modules: an automatic speech recognition (ASR) module to convert speech into text and a text topic classific…
Bidirectional Multiscale Feature Aggregation for Speaker Verification
Jiajun Qi, Wu Guo, Bin Gu
In this paper, we propose a novel bidirectional multiscale feature aggregation (BMFA) network with attentional fusion modules for text-independent speaker verification. The feature…
Gaussian speaker embedding learning for text-independent speaker verification
Bin Gu, Wu Guo
The x-vector maps segments of arbitrary duration to vectors of fixed dimension using deep neural network. Combined with the probabilistic linear discriminant analysis (PLDA) backen…
An Improved Deep Neural Network for Modeling Speaker Characteristics at Different Temporal Scales
Bin Gu, Wu Guo
This paper presents an improved deep embedding learning method based on convolutional neural network (CNN) for text-independent speaker verification. Two improvements are proposed…
Attentive batch normalization for lstm-based acoustic modeling of speech recognition
Fenglin Ding, Wu Guo, Lirong Dai +1
Batch normalization (BN) is an effective method to accelerate model training and improve the generalization performance of neural networks. In this paper, we propose an improved ba…
Attention-based gated scaling adaptative acoustic model for ctc-based speech recognition
Fenglin Ding, Wu Guo, Lirong Dai +1
In this paper, we propose a novel adaptive technique that uses an attention-based gated scaling (AGS) scheme to improve deep feature learning for connectionist temporal classificat…