Search Results for author: Mingxing Xu

Found 10 papers, 2 papers with code

Enhancing Quantised End-to-End ASR Models via Personalisation

1 code implementation17 Sep 2023 Qiuming Zhao, Guangzhi Sun, Chao Zhang, Mingxing Xu, Thomas Fang Zheng

Recent end-to-end automatic speech recognition (ASR) models have become increasingly larger, making them particularly challenging to be deployed on resource-constrained devices.

Automatic Speech Recognition Automatic Speech Recognition (ASR) +1

Hierarchical Spherical CNNs with Lifting-based Adaptive Wavelets for Pooling and Unpooling

no code implementations31 May 2022 Mingxing Xu, Chenglin Li, Wenrui Dai, Siheng Chen, Junni Zou, Pascal Frossard, Hongkai Xiong

Specifically, adaptive spherical wavelets are learned with a lifting structure that consists of trainable lifting operators (i. e., update and predict operators).

LiftPool: Lifting-based Graph Pooling for Hierarchical Graph Representation Learning

no code implementations27 Apr 2022 Mingxing Xu, Wenrui Dai, Chenglin Li, Junni Zou, Hongkai Xiong

Subsequently, this local information is aligned and propagated to the preserved nodes to alleviate information loss in graph coarsening.

Graph Classification Graph Representation Learning

Learning from Multiple Noisy Augmented Data Sets for Better Cross-Lingual Spoken Language Understanding

no code implementations EMNLP 2021 YingMei Guo, Linjun Shou, Jian Pei, Ming Gong, Mingxing Xu, Zhiyong Wu, Daxin Jiang

Although various data augmentation approaches have been proposed to synthesize training data in low-resource target languages, the augmented data sets are often noisy, and thus impede the performance of SLU models.

Data Augmentation Denoising +1

Graph Neural Networks With Lifting-based Adaptive Graph Wavelets

no code implementations3 Aug 2021 Mingxing Xu, Wenrui Dai, Chenglin Li, Junni Zou, Hongkai Xiong, Pascal Frossard

To ensure that the learned graph representations are invariant to node permutations, a layer is employed at the input of the networks to reorder the nodes according to their local topology information.

Graph Representation Learning

Guoym at SemEval-2020 Task 8: Ensemble-based Classification of Visuo-Lingual Metaphor in Memes

no code implementations SEMEVAL 2020 YingMei Guo, Jinfa Huang, Yanlong Dong, Mingxing Xu

In our system, we utilize five types of representation of data as input of base classifiers to extract information from different aspects.

FERNet: Fine-grained Extraction and Reasoning Network for Emotion Recognition in Dialogues

no code implementations Asian Chapter of the Association for Computational Linguistics 2020 YingMei Guo, Zhiyong Wu, Mingxing Xu

Unlike non-conversation scenes, emotion recognition in dialogues (ERD) poses more complicated challenges due to its interactive nature and intricate contextual information.

Emotion Recognition

Spatial-Temporal Transformer Networks for Traffic Flow Forecasting

1 code implementation9 Jan 2020 Mingxing Xu, Wenrui Dai, Chunmiao Liu, Xing Gao, Weiyao Lin, Guo-Jun Qi, Hongkai Xiong

In this paper, we propose a novel paradigm of Spatial-Temporal Transformer Networks (STTNs) that leverages dynamical directed spatial dependencies and long-range temporal dependencies to improve the accuracy of long-term traffic forecasting.

Traffic Prediction

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