Translation is a mental and intellectual activity that has always attracted the attention of linguists, literary critics, psychologists, ethnographers, etc. It well-known lexicosemantic analysis translation important precisely for where they carry out in-depth scientific research. The purpose this research to analyze lexico-semantic asymmetry in text. material study was English Tajik novel “Mem...

Most of the existing machine translations are based on word-for-word translation. The major obstacle in developing such a system is natural language is not free from ambiguity problems. One word may have more than one semantic, and vice versa. Herein, we propose a semantic-based Malay-English translation using an n-gram model. The Malay-English translation is not a word-for-word basis but is de...

The issue of meaning is undoubtedly significant in translation theory. Based on Catford’s and Nida’s view on meaning in translation, this paper aims at explore linguistic school’s contribution to the theoretical description of meaning. With Nida’s semantic studies as a focus, it argues that Nida’s semantic studies represent an important stage and carry the linguistic school’s theoretical studie...

The article reveals and scientifically explains the meaning of such concepts as leader leadership, figure, state political leader, terms in field linguistics, a separate linguistics. meanings these words various languages, particular, European Russian their semantic nuances currently existing equivalents Kazakh language are analyzed. Internet dictionaries used for this purpose, i.e. https://www...

Measuring semantic similarity is a task needed in many Natural Language Processing (NLP) applications. For example, in Machine Translation evaluation, semantic similarity is used to assess the quality of the machine translation output by measuring the degree of equivalence between a reference translation and the machine translation output. The problem of semantic similarity (Corley and Mihalcea...

To explore the potential application of semantic roles in structural machine translation, we propose to study the automatic learning of English-Chinese bilingual predicate argument structure mapping. We describe ARG ALIGN, a new model for learning bilingual semantic frames that employs monolingual Chinese and English semantic parsers to learn bilingual semantic role mappings with 72.45% Fscore,...

Using Chinese characters as an intermediate equivalent unit, we decompose machine translation into two stages, semantic translation and grammar translation. This strategy is tentatively applied to machine translation between Vietnamese and Chinese. During the semantic translation, Vietnamese syllables are one-by-one converted into the corresponding Chinese characters. During the grammar transla...