End-to-end speech translation (ST) for conversation recordings involves
...
The 5G networks have extensively promoted the growth of mobile users and...
With the development of networking technology, the computing system has
...
With the development of the Internet of Things (IoT) and the birth of va...
Deep neural networks (DNNs) have found widespread applications in
interp...
In this paper, we advocate CPN-FedSL, a novel and flexible Federated Spl...
Accurately detecting student behavior in classroom videos can aid in
ana...
Kubernetes (k8s) has the potential to coordinate distributed edge resour...
Most recently, the pathology diagnosis of cancer is shifting to integrat...
Web 3.0 pursues the establishment of decentralized ecosystems based on
b...
Patch-based physical attacks have increasingly aroused concerns.
Howev...
Deep Neural Networks (DNNs) have been extensively utilized in aerial
det...
With the drive to create a decentralized digital economy, Web 3.0 has be...
Several trade-offs need to be balanced when employing monaural speech
se...
Self-supervised learning (SSL) methods such as WavLM have shown promisin...
Multi-talker automatic speech recognition (ASR) has been studied to gene...
This paper presents a novel streaming automatic speech recognition (ASR)...
Existing multi-channel continuous speech separation (CSS) models are hea...
This paper presents a streaming speaker-attributed automatic speech
reco...
The edge-cloud system has the potential to combine the advantages of
het...
This paper proposes a token-level serialized output training (t-SOT), a ...
This paper proposes PickNet, a neural network model for real-time channe...
In the presence of heterogeneity between the randomized controlled trial...
Personalized speech enhancement (PSE) models utilize additional cues, su...
Continuous speech separation (CSS) aims to separate overlapping voices f...
Continuous speech separation using a microphone array was shown to be
pr...
This paper presents Transcribe-to-Diarize, a new approach for neural spe...
A promising approach to solving challenging long-horizon tasks has been ...
Speaker-attributed automatic speech recognition (SA-ASR) is a task to
re...
This paper presents our recent effort on end-to-end speaker-attributed
a...
Transcribing meetings containing overlapped speech with only a single di...
Speech separation has been shown effective for multi-talker speech
recog...
Kubernetes (k8s) has the potential to merge the distributed edge and the...
Edge computing-enhanced Internet of Vehicles (EC-IoV) enables ubiquitous...
An end-to-end (E2E) speaker-attributed automatic speech recognition (SA-...
Joint optimization of multi-channel front-end and automatic speech
recog...
Recently, an end-to-end speaker-attributed automatic speech recognition ...
Recently, an end-to-end (E2E) speaker-attributed automatic speech recogn...
The heterogeneity of treatment effect (HTE) lies at the heart of precisi...
We propose an end-to-end speaker-attributed automatic speech recognition...
As the 5G communication networks are being widely deployed worldwide, bo...
Parallel randomized trial (RT) and real-world (RW) data are becoming
inc...
This paper proposes serialized output training (SOT), a novel framework ...
We leverage the complementing features of randomized clinical trials (RC...
Many traditional signal recovery approaches can behave well basing on th...
The multi-stream paradigm of audio processing, in which several sources ...
Purpose: To remove retinal shadows from optical coherence tomography (OC...
Sequence-to-sequence models have been widely used in end-to-end speech
p...
The peak-to-average-power ratio (PAPR) of the frequency domain multiplex...
Ubiquitous sensors and smart devices from factories and communities guar...