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1
A comparative study of several parameterizations for speaker recognition ...
Faundez-Zanuy, Marcos. - : arXiv, 2022
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2
A Neural Pairwise Ranking Model for Readability Assessment ...
Lee, Justin; Vajjala, Sowmya. - : arXiv, 2022
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3
Compiler-Driven Simulation of Reconfigurable Hardware Accelerators ...
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4
Subspace-based Representation and Learning for Phonotactic Spoken Language Recognition ...
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5
ClassSPLOM -- A Scatterplot Matrix to Visualize Separation of Multiclass Multidimensional Data ...
Aupetit, Michael; Ali, Ahmed. - : arXiv, 2022
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6
A Deep CNN Architecture with Novel Pooling Layer Applied to Two Sudanese Arabic Sentiment Datasets ...
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7
Mono vs Multilingual BERT: A Case Study in Hindi and Marathi Named Entity Recognition ...
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8
Informative Causality Extraction from Medical Literature via Dependency-tree based Patterns ...
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9
Learning and controlling the source-filter representation of speech with a variational autoencoder ...
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10
Correcting Misproducted Speech using Spectrogram Inpainting ...
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11
WLASL-LEX: a Dataset for Recognising Phonological Properties in American Sign Language ...
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12
A Transformer-Based Contrastive Learning Approach for Few-Shot Sign Language Recognition ...
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13
Including Facial Expressions in Contextual Embeddings for Sign Language Generation ...
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14
Statistical and Spatio-temporal Hand Gesture Features for Sign Language Recognition using the Leap Motion Sensor ...
Bird, Jordan J.. - : arXiv, 2022
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15
Vision-Based American Sign Language Classification Approach via Deep Learning ...
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16
Exploring Sub-skeleton Trajectories for Interpretable Recognition of Sign Language ...
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17
Sign Language Recognition System using TensorFlow Object Detection API ...
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18
pNLP-Mixer: an Efficient all-MLP Architecture for Language ...
Abstract: Large pre-trained language models drastically changed the natural language processing(NLP) landscape. Nowadays, they represent the go-to framework to tackle diverse NLP tasks, even with a limited number of annotations. However, using those models in production, either in the cloud or at the edge, remains a challenge due to the memory footprint and/or inference costs. As an alternative, recent work on efficient NLP has shown that small weight-efficient models can reach competitive performance at a fraction of the costs. Here, we introduce pNLP-Mixer, an embbedding-free model based on the MLP-Mixer architecture that achieves high weight-efficiency thanks to a novel linguistically informed projection layer. We evaluate our model on two multi-lingual semantic parsing datasets, MTOP and multiATIS. On MTOP our pNLP-Mixer almost matches the performance of mBERT, which has 38 times more parameters, and outperforms the state-of-the-art of tiny models (pQRNN) with 3 times fewer parameters. On a long-sequence ... : Preprint ...
Keyword: Artificial Intelligence cs.AI; Computation and Language cs.CL; FOS Computer and information sciences; Machine Learning cs.LG
URL: https://arxiv.org/abs/2202.04350
https://dx.doi.org/10.48550/arxiv.2202.04350
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19
Multilingual Abusiveness Identification on Code-Mixed Social Media Text ...
Ranjan, Ekagra; Poddar, Naman. - : arXiv, 2022
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20
hate-alert@DravidianLangTech-ACL2022: Ensembling Multi-Modalities for Tamil TrollMeme Classification ...
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