When labeled data is insufficient, semi-supervised learning with the
pse...
Previous research in speech enhancement has mostly focused on modeling t...
Selecting application scenarios matching data is important for the autom...
Code-switching automatic speech recognition becomes one of the most
chal...
The complexity of heterogeneous computing architectures, as well as the
...
There is often a trade-off between performance and latency in streaming
...
The cross-domain performance of automatic speech recognition (ASR) could...
Automatic speech recognition (ASR) with federated learning (FL) makes it...
Multi-hop QA requires the machine to answer complex questions through fi...
Incremental language learning with pseudo-data can alleviate catastrophi...
Self-supervised pre-training has dramatically improved the performance o...
In this paper, the optimal source model for the independent vector analy...
This paper describes the systems submitted by team HCCL to the Far-Field...
Recently neural architecture search(NAS) has been successfully used in i...
When only a limited amount of accented speech data is available, to prom...
The deep neural network (DNN) based speech enhancement approaches have
a...
Recently, Transformer has gained success in automatic speech recognition...
This technical report describes the IOA team's submission for TASK1A of
...
Scientific applications in HPC environment are more com-plex and more
da...
A stream attention framework has been applied to the posterior probabili...
In room acoustic environments, the Relative Transfer Functions (RTFs) ar...
Multichannel linear filters, such as the Multichannel Wiener Filter (MWF...
This paper presents the contribution to the third 'CHiME' speech separat...