19 citations · 64 across the 19 of their papers we have counts for
19 papers
UBG-Net: An Uncertainty-aware Bayesian Gating Network for Robust Audio-Visual Speech Recognition
Jinjie Fu, Hang Chen, Wu Guo +3
Audio-Visual speech recognition systems often degrade in real-world scenarios due to signal corruption and distribution shifts. To address this, we propose a unified uncertainty-mo…
Pre-training Language Model as a Multi-perspective Course Learner
Beiduo Chen, Shaohan Huang, Zihan Zhang +6
ELECTRA, the generator-discriminator pre-training framework, has achieved impressive semantic construction capability among various downstream tasks. Despite the convincing perform…
Language-Universal Adapter Learning with Knowledge Distillation for End-to-End Multilingual Speech Recognition
Zhijie Shen, Wu Guo, Bin Gu
In this paper, we propose a language-universal adapter learning framework based on a pre-trained model for end-to-end multilingual automatic speech recognition (ASR). For acoustic…
USTC-NELSLIP at SemEval-2022 Task 11: Gazetteer-Adapted Integration Network for Multilingual Complex Named Entity Recognition
Beiduo Chen, Jun-Yu Ma, Jiajun Qi +3
This paper describes the system developed by the USTC-NELSLIP team for SemEval-2022 Task 11 Multilingual Complex Named Entity Recognition (MultiCoNER). We propose a gazetteer-adapt…
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…
Improved Meta-Learning Training for Speaker Verification
Yafeng Chen, Wu Guo, Bin Gu
Meta-learning has recently become a research hotspot in speaker verification (SV). We introduce two methods to improve the meta-learning training for SV in this paper. For the firs…
Multi-task Metric Learning for Text-independent Speaker Verification
Yafeng Chen, Wu Guo, Jingjing Shi +2
In this work, we introduce metric learning (ML) to enhance the deep embedding learning for text-independent speaker verification (SV). Specifically, the deep speaker embedding netw…
Exploring Universal Speech Attributes for Speaker Verification with an Improved Cross-stitch Network
Jiajun Qi, Wu Guo, Jingjing Shi +2
The universal speech attributes for x-vector based speaker verification (SV) are addressed in this paper. The manner and place of articulation form the fundamental speech attribute…
An Adaptive X-vector Model for Text-independent Speaker Verification
Bin Gu, Wu Guo, Lirong Dai +1
In this paper, adaptive mechanisms are applied in deep neural network (DNN) training for x-vector-based text-independent speaker verification. First, adaptive convolutional neural…
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…
Deep Neural Network Embeddings with Gating Mechanisms for Text-Independent Speaker Verification
Lanhua You, Wu Guo, Lirong Dai +1
In this paper, gating mechanisms are applied in deep neural network (DNN) training for x-vector-based text-independent speaker verification. First, a gated convolution neural netwo…
Multi-Task Learning with High-Order Statistics for X-vector based Text-Independent Speaker Verification
Lanhua You, Wu Guo, Lirong Dai +1
The x-vector based deep neural network (DNN) embedding systems have demonstrated effectiveness for text-independent speaker verification. This paper presents a multi-task learning…
USTCSpeech System for VOiCES from a Distance Challenge 2019
Lanhua You, Bin Gu, Wu Guo
This document describes the speaker verification systems developed in the Speech lab at the University of Science and Technology of China (USTC) for the VOiCES from a Distance Chal…
The USTC-NEL Speech Translation system at IWSLT 2018
Dan Liu, Junhua Liu, Wu Guo +5
This paper describes the USTC-NEL system to the speech translation task of the IWSLT Evaluation 2018. The system is a conventional pipeline system which contains 3 modules: speech…
Integrate Document Ranking Information into Confidence Measure Calculation for Spoken Term Detection
Quan Liu, Wu Guo, Zhen-Hua Ling
This paper proposes an algorithm to improve the calculation of confidence measure for spoken term detection (STD). Given an input query term, the algorithm first calculates a measu…