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20172020
most citedWorse WER, but Better BLEU? Leveraging Word Embedding as Intermediate in Multitask End-to-End Speech Translation

2 citations · 2 across the 4 of their papers we have counts for

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Showing 2019Show all

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cs.CL2019

Training a code-switching language model with monolingual data

Shun-Po Chuang, Tzu-Wei Sung, Hung-Yi Lee

A lack of code-switching data complicates the training of code-switching (CS) language models. We propose an approach to train such CS language models on monolingual data only. By…

cs.CL2019

Sequence-to-sequence Automatic Speech Recognition with Word Embedding Regularization and Fused Decoding

Alexander H. Liu, Tzu-Wei Sung, Shun-Po Chuang +2

In this paper, we investigate the benefit that off-the-shelf word embedding can bring to the sequence-to-sequence (seq-to-seq) automatic speech recognition (ASR). We first introduc…