Vectorial representations of words have grown remarkably popular in natural language processing and machine translation. The recent surge in deep learning-inspired methods for producing distributed representations has been widely noted even outside these fields. Existing representations are typically trained on large monolingual corpora using context-based prediction models. In this paper, we p...

This paper explores a new approach to help non-expert users with no background in linguistics to add new words to a monolingual dictionary in a rule-based machine translation system. Our method aims at choosing the correct paradigm which explains not only the particular surface form introduced by the user, but also the rest of inflected forms of the word. A large monolingual corpus is used to e...

Objectives: The purpose of this research was to explore the possible differences in the working memory of monolingual (Persian) and bilingual  (Persian-Baluchi) children. We wanted to examine if there is a statistically significant relationship between working memory and bilingualism. Methods: Four working memory (WM) tests, assessing three WM components, were administered to 140 second...

Targeted paraphrasing is a new approach to the problem of obtaining cost-effective, reasonable quality translation that makes use of simple and inexpensive human computations by monolingual speakers in combination with machine translation. The key insight behind the process is that it is possible to spot likely translation errors with only monolingual knowledge of the target language, and it is...

Crosslingual word embeddings represent lexical items from different languages in the same vector space, enabling transfer of NLP tools. However, previous attempts had expensive resource requirements, difficulty incorporating monolingual data or were unable to handle polysemy. We address these drawbacks in our method which takes advantage of a high coverage dictionary in an EM style training alg...

We present a research on learning Indonesian-Chinese bilingual lexicon using monolingual word embedding and bilingual seed lexicons to build shared bilingual word embedding space. We take the first attempt to examine the impact of different monolingual signals for the choice of seed lexicons on the model performance. We found that although monolingual signals alone do not seem to outperform sig...

There is an increasing need to deploy speech recognition systems supporting multiple languages/dialects on portable devices worldwide. A common approach uses a collection of individual monolingual speech recognition systems as a solution. However, such an approach is not practical for handheld devices such as cell phones due to stringent restrictions on memory and computational resources. In th...

In TREC 2002 the Berkeley group participated only in the English-Arabic cross-language retrieval (CLIR) track. One Arabic monolingual run and three English-Arabic cross-language runs were submitted. Our approach to the crosslanguage retrieval was to translate the English topics into Arabic using online English-Arabic machine translation systems. The four official runs are named as BKYMON, BKYCL...

This paper describes our independent effort for extending the monolingual semantic textual similarity (STS) task setting to multiple cross-lingual settings involving English, Japanese, and Chinese. So far, we have adopted a “monolingual similarity after translation” strategy to predict the semantic similarity between a pair of sentences in different languages. With this strategy, a monolingual ...