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Found 13 papers, 0 papers with code
Accelerating PDE Data Generation via Differential Operator Action in Solution Space
It applies differential operators on these solutions, a process we call 'operator action', to efficiently generate precise PDE data points.
BC4LLM: Trusted Artificial Intelligence When Blockchain Meets Large Language Models
Moreover, the content generated by LLMs is difficult to identify and trace, and it is difficult to cross-platform mutual recognition.
Dynamic Alignment Mask CTC: Improved Mask-CTC with Aligned Cross Entropy
Because of predicting all the target tokens in parallel, the non-autoregressive models greatly improve the decoding efficiency of speech recognition compared with traditional autoregressive models.
Speech Augmentation Based Unsupervised Learning for Keyword Spotting
In our experiments, with augmentation based unsupervised learning, our KWS model achieves better performance than other unsupervised methods, such as CPC, APC, and MPC.
Adaptive Activation Network For Low Resource Multilingual Speech Recognition
The existing models mostly established a bottleneck (BN) layer by pre-training on a large source language, and transferring to the low resource target language.
Automatic Speech Recognition
Automatic Speech Recognition (ASR)
+1
Dropout Regularization for Self-Supervised Learning of Transformer Encoder Speech Representation
We evaluated the proposed methods on phoneme classification and speaker recognition tasks.
Loss Prediction: End-to-End Active Learning Approach For Speech Recognition
End-to-end speech recognition systems usually require huge amounts of labeling resource, while annotating the speech data is complicated and expensive.
Unidirectional Memory-Self-Attention Transducer for Online Speech Recognition
We propose a novel network structure, called Memory-Self-Attention (MSA) Transducer.
Low Latency Scheduling Algorithms for Full-Duplex V2X Networks
Vehicular communication systems have been an active subject of research for many years and are important technologies in the 5G and the post-5G era.
Autonomous Driving
Information Theory
Signal Processing
Information Theory
MLNET: An Adaptive Multiple Receptive-field Attention Neural Network for Voice Activity Detection
The MLNET leveraged multi-branches to extract multiple contextual speech information and investigated an effective attention block to weight the most crucial parts of the context for final classification.
Some Supplementaries to The Counting Semantics for Abstract Argumentation
Dung's abstract argumentation framework consists of a set of interacting arguments and a series of semantics for evaluating them.
Attacker and Defender Counting Approach for Abstract Argumentation
In this paper, we propose a counting approach for a more fine-gained assessment to arguments by counting the number of their respective attackers and defenders based on argument graph and argument game.
Argument Ranking with Categoriser Function
Recently, ranking-based semantics is proposed to rank-order arguments from the most acceptable to the weakest one(s), which provides a graded assessment to arguments.
