63 citations · 235 across the 37 of their papers we have counts for
37 papers
Symmetric Saliency-based Adversarial Attack To Speaker Identification
Jiadi Yao, Xing Chen, Xiao-Lei Zhang +2
Adversarial attack approaches to speaker identification either need high computational cost or are not very effective, to our knowledge. To address this issue, in this paper, we pr…
Deep Learning Based Stage-wise Two-dimensional Speaker Localization with Large Ad-hoc Microphone Arrays
Shupei Liu, Linfeng Feng, Yijun Gong +4
While deep-learning-based speaker localization has shown advantages in challenging acoustic environments, it often yields only direction-of-arrival (DOA) cues rather than precise t…
Conformer-based End-to-end Speech Recognition With Rotary Position Embedding
Shengqiang Li, Menglong Xu, Xiao-Lei Zhang
Transformer-based end-to-end speech recognition models have received considerable attention in recent years due to their high training speed and ability to model a long-range globa…
AUC Optimization for Robust Small-footprint Keyword Spotting with Limited Training Data
Menglong Xu, Shengqiang Li, Chengdong Liang +1
Deep neural networks provide effective solutions to small-footprint keyword spotting (KWS). However, if training data is limited, it remains challenging to achieve robust and highl…
fMBN-E: Efficient Unsupervised Network Structure Ensemble and Selection for Clustering
Xiao-Lei Zhang
It is known that unsupervised nonlinear dimensionality reduction and clustering is sensitive to the selection of hyperparameters, particularly for deep learning based methods, whic…
Attention-based multi-channel speaker verification with ad-hoc microphone arrays
Chengdong Liang, Junqi Chen, Shanzheng Guan +1
Recently, ad-hoc microphone array has been widely studied. Unlike traditional microphone array settings, the spatial arrangement and number of microphones of ad-hoc microphone arra…
Efficient conformer-based speech recognition with linear attention
Shengqiang Li, Menglong Xu, Xiao-Lei Zhang
Recently, conformer-based end-to-end automatic speech recognition, which outperforms recurrent neural network based ones, has received much attention. Although the parallel computi…
Scaling sparsemax based channel selection for speech recognition with ad-hoc microphone arrays
Junqi Chen, Xiao-Lei Zhang
Recently, speech recognition with ad-hoc microphone arrays has received much attention. It is known that channel selection is an important problem of ad-hoc microphone arrays, howe…
Transformer-based end-to-end speech recognition with residual Gaussian-based self-attention
Chengdong Liang, Menglong Xu, Xiao-Lei Zhang
Self-attention (SA), which encodes vector sequences according to their pairwise similarity, is widely used in speech recognition due to its strong context modeling ability. However…
Deep NMF Topic Modeling
JianYu Wang, Xiao-Lei Zhang
Nonnegative matrix factorization (NMF) based topic modeling methods do not rely on model- or data-assumptions much. However, they are usually formulated as difficult optimization p…
Minimum-volume Multichannel Nonnegative matrix factorization for blind source separation
Jianyu Wang, Shanzheng Guan, Shupei Liu +1
Multichannel blind audio source separation aims to recover the latent sources from their multichannel mixtures without supervised information. One state-of-the-art blind audio sour…
Speaker Recognition Based on Deep Learning: An Overview
Zhongxin Bai, Xiao-Lei Zhang
Speaker recognition is a task of identifying persons from their voices. Recently, deep learning has dramatically revolutionized speaker recognition. However, there is lack of compr…
Deep Ad-hoc Beamforming Based on Speaker Extraction for Target-Dependent Speech Separation
Ziye Yang, Shanzheng Guan, Xiao-Lei Zhang
Recently, the research on ad-hoc microphone arrays with deep learning has drawn much attention, especially in speech enhancement and separation. Because an ad-hoc microphone array…
A comparison of handcrafted, parameterized, and learnable features for speech separation
Wenbo Zhu, Mou Wang, Xiao-Lei Zhang +1
The design of acoustic features is important for speech separation. It can be roughly categorized into three classes: handcrafted, parameterized, and learnable features. Among them…
Speech enhancement aided end-to-end multi-task learning for voice activity detection
Xu Tan, Xiao-Lei Zhang
Robust voice activity detection (VAD) is a challenging task in low signal-to-noise (SNR) environments. Recent studies show that speech enhancement is helpful to VAD, but the perfor…
Transformer-based End-to-End Speech Recognition with Local Dense Synthesizer Attention
Menglong Xu, Shengqiang Li, Xiao-Lei Zhang
Recently, several studies reported that dot-product selfattention (SA) may not be indispensable to the state-of-theart Transformer models. Motivated by the fact that dense synthesi…
Depthwise Separable Convolutional ResNet with Squeeze-and-Excitation Blocks for Small-footprint Keyword Spotting
Menglong Xu, Xiao-Lei Zhang
One difficult problem of keyword spotting is how to miniaturize its memory footprint while maintain a high precision. Although convolutional neural networks have shown to be effect…
Partial AUC optimization based deep speaker embeddings with class-center learning for text-independent speaker verification
Zhongxin Bai, Xiao-Lei Zhang, Jingdong Chen
Deep embedding based text-independent speaker verification has demonstrated superior performance to traditional methods in many challenging scenarios. Its loss functions can be gen…
Learning deep representations by multilayer bootstrap networks for speaker diarization
Meng-Zhen Li, Xiao-Lei Zhang
The performance of speaker diarization is strongly affected by its clustering algorithm at the test stage. However, it is known that clustering algorithms are sensitive to random n…
Deep topic modeling by multilayer bootstrap network and lasso
Jianyu Wang, Xiao-Lei Zhang
Topic modeling is widely studied for the dimension reduction and analysis of documents. However, it is formulated as a difficult optimization problem. Current approximate solutions…
Multi-channel Speech Separation Using Deep Embedding Model with Multilayer Bootstrap Networks
Ziye Yang, Xiao-Lei Zhang
Recently, deep clustering (DPCL) based speaker-independent speech separation has drawn much attention, since it needs little speaker prior information. However, it still has much r…
Speaker Verification By Partial AUC Optimization With Mahalanobis Distance Metric Learning
Zhongxin Bai, Xiao-Lei Zhang, Jingdong Chen
Receiver operating characteristic (ROC) and detection error tradeoff (DET) curves are two widely used evaluation metrics for speaker verification. They are equivalent since the lat…
Deep Ad-hoc Beamforming
Xiao-Lei Zhang
Far-field speech processing is an important and challenging problem. In this paper, we propose \textit{deep ad-hoc beamforming}, a deep-learning-based multichannel speech enhanceme…
Linear Regression for Speaker Verification
Xiao-Lei Zhang
This paper presents a linear regression based back-end for speaker verification. Linear regression is a simple linear model that minimizes the mean squared estimation error between…