44 citations · 104 across the 9 of their papers we have counts for
9 papers
TouchASP: Elastic Automatic Speech Perception that Everyone Can Touch
Xingchen Song, Chengdong Liang, Binbin Zhang +9
Large Automatic Speech Recognition (ASR) models demand a vast number of parameters, copious amounts of data, and significant computational resources during the training process. Ho…
WeKws: A production first small-footprint end-to-end Keyword Spotting Toolkit
Jie Wang, Menglong Xu, Jingyong Hou +4
Keyword spotting (KWS) enables speech-based user interaction and gradually becomes an indispensable component of smart devices. Recently, end-to-end (E2E) methods have become the m…
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…
Libri-adhoc40: A dataset collected from synchronized ad-hoc microphone arrays
Shanzheng Guan, Shupei Liu, Junqi Chen +8
Recently, there is a research trend on ad-hoc microphone arrays. However, most research was conducted on simulated data. Although some data sets were collected with a small number…
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…
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…
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…