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Found 20 papers, 2 papers with code
PaMMA-Net: Plasmas magnetic measurement evolution based on data-driven incremental accumulative prediction
An accurate evolution model is crucial for effective control and in-depth study of fusion plasmas.
Dynamics-incorporated Modeling Framework for Stability Constrained Scheduling Under High-penetration of Renewable Energy
In this paper, a modularized modeling framework is designed to enable a dynamics-incorporated power system scheduling under high-penetration of renewable energy.
MVANet: Multi-Stage Video Attention Network for Sound Event Localization and Detection with Source Distance Estimation
We propose a novel output representation that combines the DOA with distance of sound sources by calculating the real Cartesian coordinates to address the newly introduced source distance estimation (SDE) task in the Detection and Classification of Acoustic Scenes and Events (DCASE) 2024 Challenge.
The USTC-NERCSLIP Systems for The ICMC-ASR Challenge
This report describes the submitted system to the In-Car Multi-Channel Automatic Speech Recognition (ICMC-ASR) challenge, which considers the ASR task with multi-speaker overlapping and Mandarin accent dynamics in the ICMC case.
Equity-aware Load Shedding Optimization
Load shedding is usually the last resort to balance generation and demand to maintain stable operation of the electric grid after major disturbances.
Exploring Audio-Visual Information Fusion for Sound Event Localization and Detection In Low-Resource Realistic Scenarios
Evaluation results on the Detection and Classification of Acoustic Scenes and Events (DCASE) 2023 Challenge data set demonstrate significant improvements in SELD performances.
Multitask frame-level learning for few-shot sound event detection
This paper focuses on few-shot Sound Event Detection (SED), which aims to automatically recognize and classify sound events with limited samples.
Stable Relay Learning Optimization Approach for Fast Power System Production Cost Minimization Simulation
The proposed approach shows stable performance, reducing fluctuations by approximately 50% compared with IL.
SegRap2023: A Benchmark of Organs-at-Risk and Gross Tumor Volume Segmentation for Radiotherapy Planning of Nasopharyngeal Carcinoma
The precise delineation of Gross Tumor Volumes (GTVs) and Organs-At-Risk (OARs) is crucial in radiation treatment, directly impacting patient prognosis.
AST-SED: An Effective Sound Event Detection Method Based on Audio Spectrogram Transformer
In this paper, we propose an effective sound event detection (SED) method based on the audio spectrogram transformer (AST) model, pretrained on the large-scale AudioSet for audio tagging (AT) task, termed AST-SED.
Deep Virtual-to-Real Distillation for Pedestrian Crossing Prediction
To this end, we formulate a deep virtual to real distillation framework by introducing the synthetic data that can be generated conveniently, and borrow the abundant information of pedestrian movement in synthetic videos for the pedestrian crossing prediction in real data with a simple and lightweight implementation.
A Unified Analytical Method to Quantify Three Types of Fast Frequency Response from Inverter-based Resources
The simulation results in the IEEE 39-bus system with different types of FFR demonstrate that the proposed method provides an accurate and fast prediction of the frequency nadir under various disturbances.
DLMP of Competitive Markets in Active Distribution Networks: Models, Solutions, Applications, and Visions
The DLMP provides a solution that can be essential for competitive market operation in future distribution systems.
A Complementary Joint Training Approach Using Unpaired Speech and Text for Low-Resource Automatic Speech Recognition
Unpaired data has shown to be beneficial for low-resource automatic speech recognition~(ASR), which can be involved in the design of hybrid models with multi-task training or language model dependent pre-training.
Automatic Speech Recognition
Automatic Speech Recognition (ASR)
+3
Learning Contextually Fused Audio-visual Representations for Audio-visual Speech Recognition
The proposed approach explores both the complementarity of audio-visual modalities and long-term context dependency using a transformer-based fusion module and a flexible masking strategy.
A Noise-Robust Self-supervised Pre-training Model Based Speech Representation Learning for Automatic Speech Recognition
In this work, we therefore first analyze the noise robustness of wav2vec2. 0 via experiments.
Automatic Speech Recognition
Automatic Speech Recognition (ASR)
+3
Impact of DER Communication Delay in AGC: Cyber-Physical Dynamic Simulation
Distributed energy resource (DER) frequency regulations are promising technologies for future grid operation.
USTC-NELSLIP System Description for DIHARD-III Challenge
This system description describes our submission system to the Third DIHARD Speech Diarization Challenge.
XLST: Cross-lingual Self-training to Learn Multilingual Representation for Low Resource Speech Recognition
In this paper, we propose a weakly supervised multilingual representation learning framework, called cross-lingual self-training (XLST).
Effective Parallelism for Equation and Jacobian Evaluation in Power Flow Calculation
This letter investigates parallelism approaches for equation and Jacobian evaluations in large-scale power flow calculation.
