We present techniques for improving domainspecific translation quality with a relatively high OOV ratio on test data sets. The key idea is to maximize the vocabulary coverage without degrading the translation quality. We maximize vocabulary coverage by segmenting a word into a sequence of morphemes, prefix*-stem-suffix* and by adding a large amount of out-of-domain training corpora. To preserve...

We present techniques for improving domainspecific translation quality with a relatively high OOV ratio on test data sets. The key idea is to maximize the vocabulary coverage without degrading the translation quality. We maximize vocabulary coverage by segmenting a word into a sequence of morphemes, prefix*-stem-suffix* and by adding a large amount of out-of-domain training corpora. To preserve...

In this paper, we enhance the attention-based neural machine translation (NMT) by adding explicit coverage embedding models to alleviate issues of repeating and dropping translations in NMT. For each source word, our model starts with a full coverage embedding vector to track the coverage status, and then keeps updating it with neural networks as the translation goes. Experiments on the large-s...

This paper describes an attempt to improve the coverage of an existing name pronunciation dictionary by modelling variation in spelling. This is done by the derivation of string rewrite rules which operate on out-of-vocabulary words to map them to in-vocabulary words. These string rewrite rules are derived automatically, and are “pronunciation-neutral” in the sense that the mappings they perfor...

This study presents a method that assesses ESL learners’ vocabulary usage to improve an automated scoring system of spontaneous speech responses by non-native English speakers. Focusing on vocabulary sophistication, we estimate the difficulty of each word in the vocabulary based on its frequency in a reference corpus and assess the mean difficulty level of the vocabulary usage across the respon...

In this work, we propose a novel method for vocabulary selection which enables simultaneous speech recognition systems for lectures to automatically adapt to the diverse topics that occur in educational and scientific lectures. Utilizing materials that are available before the lecture begins, such as lecture slides, our proposed framework iteratively searches for related documents on the World ...

the current study is an attempt to investigate the particular role learners' vocabulary knowledge plays in their reading comprehension performance. it intends to determine whether breadth and depth of vocabulary knowledge are related to efl learners' reading comprehension, and to investigate which one of these variables, that is, depth or breadth of vocabulary knowledge, makes a more important ...

Developing high-quality transcription systems for very large vocabulary corpora is a challenging task. Proper names are usually key to understanding the information contained in a document. To increase the vocabulary coverage, a huge amount of text data should be used. In this paper, we extend the previously proposed neural networks for word embedding models: word vector representation proposed...