27 citations · 140 across the 12 of their papers we have counts for
9 papers · 1 filter
Automatic Speech Recognition Datasets in Cantonese: A Survey and New Dataset
Tiezheng Yu, Rita Frieske, Peng Xu +9
Automatic speech recognition (ASR) on low resource languages improves the access of linguistic minorities to technological advantages provided by artificial intelligence (AI). In t…
Contrastive Document Representation Learning with Graph Attention Networks
Peng Xu, Xinchi Chen, Xiaofei Ma +2
Recent progress in pretrained Transformer-based language models has shown great success in learning contextual representation of text. However, due to the quadratic self-attention…
Attention-guided Generative Models for Extractive Question Answering
Peng Xu, Davis Liang, Zhiheng Huang +1
We propose a novel method for applying Transformer models to extractive question answering (QA) tasks. Recently, pretrained generative sequence-to-sequence (seq2seq) models have ac…
Multiplicative Position-aware Transformer Models for Language Understanding
Zhiheng Huang, Davis Liang, Peng Xu +1
Transformer models, which leverage architectural improvements like self-attention, perform remarkably well on Natural Language Processing (NLP) tasks. The self-attention mechanism…
Cross-lingual Spoken Language Understanding with Regularized Representation Alignment
Zihan Liu, Genta Indra Winata, Peng Xu +2
Despite the promising results of current cross-lingual models for spoken language understanding systems, they still suffer from imperfect cross-lingual representation alignments be…
Improve Transformer Models with Better Relative Position Embeddings
Zhiheng Huang, Davis Liang, Peng Xu +1
Transformer architectures rely on explicit position encodings in order to preserve a notion of word order. In this paper, we argue that existing work does not fully utilize positio…