Mastering a second language as a theoretical and linguodidactic problem in the aspect of neuro-linguistics

This article arose from the need to comprehend, firstly, methodological and linguodidactic problems (by linguodidactics we understand the principles of language description for learning purposes) to mastering any non-native language, not only widespread foreign languages, and, secondly, from the need to comprehend not only the teaching of a second foreign language itself but also the content of training professionals of a second foreign language (students of universities and faculties of foreign languages). Theoretical and methodological problems associated with mastering any non-native language are especially acute when we are dealing not with the first, but with the second, third, etc. non-native language. This may be a second foreign language (for example, at school), a second foreign language as the language of a pedagogical specialty (for example, at a pedagogical university), the language of ethnic (self) identification (among members of national diasporas), etc. Therefore, in this paper, along with discussing general issues of mastering a non-native language, we focus on various situations of teaching a language as a second non-native.

Elastic CRFs for Open-Ontology Slot Filling

Slot filling is a crucial component in task-oriented dialog systems that is used to parse (user) utterances into semantic concepts called slots. An ontology is defined by the collection of slots and the values that each slot can take. The most widely used practice of treating slot filling as a sequence labeling task suffers from two main drawbacks. First, the ontology is usually pre-defined and fixed and therefore is not able to detect new labels for unseen slots. Second, the one-hot encoding of slot labels ignores the correlations between slots with similar semantics, which makes it difficult to share knowledge learned across different domains. To address these problems, we propose a new model called elastic conditional random field (eCRF), where each slot is represented by the embedding of its natural language description and modeled by a CRF layer. New slot values can be detected by eCRF whenever a language description is available for the slot. In our experiment, we show that eCRFs outperform existing models in both in-domain and cross-domain tasks, especially in predicting unseen slots and values.

Truncated attention mechanism and cascade loss for cross-modal person re-identification

Person re-identification with natural language description is a process of retrieving the corresponding person’s image from an image dataset according to a text description of the person. The key challenge in this cross-modal task is to extract visual and text features and construct loss functions to achieve cross-modal matching between text and image. Firstly, we designed a two-branch network framework for person re-identification with natural language description. In this framework we include the following: a Bi-directional Long Short-Term Memory (Bi-LSTM) network is used to extract text features and a truncated attention mechanism is proposed to select the principal component of the text features; a MobileNet is used to extract image features. Secondly, we proposed a Cascade Loss Function (CLF), which includes cross-modal matching loss and single modal classification loss, both with relative entropy function, to fully exploit the identity-level information. The experimental results on the CUHK-PEDES dataset demonstrate that our method achieves better results in Top-5 and Top-10 than other current 10 state-of-the-art algorithms.

Linguistic processor integration for solving planimetric problems

The research deals with the original algorithms of the linguistic processor integration for solving planimetric problems. The linguistic processor translates the natural language description of the problem into a semantic representation based on the ontology that supports the axiomatics of geometry. The linguistic processor synthesizes natural-language comments to the solution and drawing objects. The method of interactive visualization of the linguistic processor functioning is proposed. The method provides a step-by-step dialog control of syntactic structure construction and its display in semantic representation. During the experiments, several dozens of standard syntactic structures correctly displayed in the semantic structures of the subject area were obtained. The direction of further research related to the development of the proposed approach is outlined.

Linguistic Processor Integration for Solving Planimetric Problems

The research deals with the original algorithms of the linguistic processor integration for solving planimetric problems. The linguistic processor translates the natural language description of the problem into a semantic representation based on the ontology that supports the axiomatics of geometry. The linguistic processor synthesizes natural-language comments to the solution and drawing objects. The method of interactive visualization of the linguistic processor functioning is proposed. The method provides a step-by-step dialog control of syntactic structure construction and its display in semantic representation. During the experiments, several dozens of standard syntactic structures correctly displayed in the semantic structures of the subject area were obtained. The direction of further research related to the development of the proposed approach is outlined.

Linguistic processor of the integrated system for solving planimetric problems

The paper deals with the original algorithms of the linguistic processor of the integrated system for solving planimetric problems. The algorithms successfully combine the method of synonymic transformations with the extended method of regular expressions processing. The linguistic processor translates the natural language description of the problem into a semantic representation based on the ontology that supports the axiomatics of geometry. Linguistic processor synthesizes natural-language comments to the solution and drawing objects. The method of interactive visualization of the linguistic processor functioning is proposed. The method provides a step-by-step dialog control of syntactic structure construction and its display in semantic representation. The results of the experimental study of the linguistic processor are interpreted. The direction of further research related to the development of the proposed approach is outlined.