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20162024
most citedSyntactic and Semantic Features For Code-Switching Factored Language Models

70 citations · 180 across the 53 of their papers we have counts for

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Showing 2016Show all

5 papers · 1 filter

cs.CL2016★ 3 cited

Challenges of Computational Processing of Code-Switching

Özlem Çetinoğlu, Sarah Schulz, Ngoc Thang Vu

This paper addresses challenges of Natural Language Processing (NLP) on non-canonical multilingual data in which two or more languages are mixed. It refers to code-switching which…

cs.CL2016★ 3 cited

Neural-based Noise Filtering from Word Embeddings

Kim Anh Nguyen, Sabine Schulte im Walde, Ngoc Thang Vu

Word embeddings have been demonstrated to benefit NLP tasks impressively. Yet, there is room for improvement in the vector representations, because current word embeddings typicall…

cs.CL2016

Sequential Convolutional Neural Networks for Slot Filling in Spoken Language Understanding

Ngoc Thang Vu

We investigate the usage of convolutional neural networks (CNNs) for the slot filling task in spoken language understanding. We propose a novel CNN architecture for sequence labeli…

cs.CL2016

Integrating Distributional Lexical Contrast into Word Embeddings for Antonym-Synonym Distinction

Kim Anh Nguyen, Sabine Schulte im Walde, Ngoc Thang Vu

We propose a novel vector representation that integrates lexical contrast into distributional vectors and strengthens the most salient features for determining degrees of word simi…

cs.CL2016

Combining Recurrent and Convolutional Neural Networks for Relation Classification

Ngoc Thang Vu, Heike Adel, Pankaj Gupta +1

This paper investigates two different neural architectures for the task of relation classification: convolutional neural networks and recurrent neural networks. For both models, we…