Towards a localist–connectionist model of word translation

2012 ◽  
pp. 135-153 ◽  
Author(s):  
Ton Dijkstra ◽  
Steven Rekké
Keyword(s):  
Connectionist Model ◽  
Word Translation

Multilink: a computational model for bilingual word recognition and word translation

2018 ◽  
Vol 22 (04) ◽  
pp. 657-679 ◽  
Author(s):  
TON DIJKSTRA ◽  
ALEXANDER WAHL ◽  
FRANKA BUYTENHUIJS ◽  
NINO VAN HALEM ◽  
ZINA AL-JIBOURI ◽  
...  
Keyword(s):  
Word Recognition ◽  
Semantic Processing ◽  
Word Production ◽  
Connectionist Model ◽  
Word Comprehension ◽  
Reference Framework ◽  
Basic Assumptions ◽  
Lexical Similarity ◽  
Word Translation ◽  
Direction Model

The computational BIA+ model (Dijkstra & Van Heuven, 2002) has provided a useful account for bilingual word recognition, while the verbal (pre-quantitative) RHM (Kroll & Stewart, 1994) has often served as a reference framework for bilingual word production and translation. According to Brysbaert and Duyck (2010), a strong need is felt for a unified implemented account of bilingual word comprehension, lexical-semantic processing, and word production. With this goal in mind, we built a localist-connectionist model, called Multilink, which integrates basic assumptions of both BIA+ and RHM. It simulates the recognition and production of cognates (form-similar translation equivalents) and non-cognates of different lengths and frequencies in tasks like monolingual and bilingual lexical decision, word naming, and word translation production. It also considers effects of lexical similarity, cognate status, relative L2-proficiency, and translation direction. Model-to-model comparisons show that Multilink provides higher correlations with empirical data than both IA and BIA+ models.

Towards a localist-connectionist model of word translation

2010 ◽  
Vol 5 (3) ◽  
pp. 401-420 ◽  
Author(s):  
Ton Dijkstra ◽  
Steven Rekké
Keyword(s):  
Word Recognition ◽  
Lexical Decision ◽  
Hierarchical Model ◽  
Connectionist Model ◽  
L2 Proficiency ◽  
Proficiency Levels ◽  
Complex Process ◽  
Word Translation ◽  
Interactive Activation ◽  
Verbal Model

Word translation is among the most sophisticated skills that bilinguals can perform. Brysbaert and Duyck (2010) have argued that the Revised Hierarchical Model (RHM; Kroll & Stewart, 1994), a verbal model for word translation in beginning and proficient bilinguals, should be abandoned in favor of connectionist models such as the Bilingual Interactive Activation Plus model (BIA+; Dijkstra & Van Heuven, 2002). However, the partially implemented BIA+ model for bilingual word recognition has neither been applied to bilinguals of different proficiency levels nor extended to the complex process of word translation. After considering a number of aspects of the RHM, a new localist-connectionist model, called Multilink, is formulated to account for the performance of bilinguals differing in their L2 proficiency in different tasks: lexical decision, language decision, and word translation.

Using Connectionist Modules for Decision Support

1990 ◽  
Vol 29 (03) ◽  
pp. 167-181 ◽  
Author(s):  
G. Hripcsak
Keyword(s):  
Decision Support ◽  
Standard Deviation ◽  
Confidence Interval ◽  
Posterior Probability ◽  
Back Propagation ◽  
Connectionist Model ◽  
Test Set ◽  
The Third ◽  
Independent Test ◽  
Better Than

AbstractA connectionist model for decision support was constructed out of several back-propagation modules. Manifestations serve as input to the model; they may be real-valued, and the confidence in their measurement may be specified. The model produces as its output the posterior probability of disease. The model was trained on 1,000 cases taken from a simulated underlying population with three conditionally independent manifestations. The first manifestation had a linear relationship between value and posterior probability of disease, the second had a stepped relationship, and the third was normally distributed. An independent test set of 30,000 cases showed that the model was better able to estimate the posterior probability of disease (the standard deviation of residuals was 0.046, with a 95% confidence interval of 0.046-0.047) than a model constructed using logistic regression (with a standard deviation of residuals of 0.062, with a 95% confidence interval of 0.062-0.063). The model fitted the normal and stepped manifestations better than the linear one. It accommodated intermediate levels of confidence well.

THE TRANSLATION STRATEGIES OF METAPHOR IN THE MAGIC OF THINKING BIG TRANSLATED INTO BAHASA INDONESIA BY DIAN PARAMESTI BAHAR

2018 ◽  
Vol 14 (3) ◽  
Author(s):  
Khairani Hayat Situmorang ◽  
I. W. Dirgeyasa ◽  
Zainuddin Zainuddin
Keyword(s):  
Data Analysis ◽  
Target Language ◽  
Qualitative Design ◽  
Translation Strategies ◽  
Source Language ◽  
Free Translation ◽  
Dead Metaphor ◽  
Word Translation ◽  
Bahasa Indonesia ◽  
Communicative Translation

The research dealt with Metaphor Sentences. The aims of this study were: (1) to find out the translation strategies of metaphors are used in The Magic of Thinking Big and (2) to describe the translation strategies maintain metaphors in The Magic of Thinking Big. The research was conducted by using qualitative design. The data of this study were sentences. The data were collected through documentary technique and the instrument was the documentary sheet. The technique of data analysis was descriptive. The finding of this study revealed that: (1) The metaphor in The magic of Thinking Big were translated by applying six translation strategies, namely: word for word Translation (5.3%) lieral translation (4.3%), faithful translation (57.5%), Free translation (3.2%), communicative translation (30.5%) and discursive creation was found (2.2%). (2) The metaphors are maintained that found in the Magic of Thinking Big are original metaphors turned into another original metaphors, stock metaphors turned into another stock metaphors, adapted metaphors turned into adapted metaphors, dead metaphors turned into dead metaphors, original metaphor turned into stock metaphor, stock metaphor turned into original metaphor, meanwhile, 10 original metaphors and 1 dead metaphor are no longer classified as metaphors. Language has special characteristic that is metaphor sentences, therefore in the case of translating of metaphor sentences in which their concept in unknown for readers, the translator often faces the problems to find out the translation strategies to translate metaphor in a source language (SL) and how the metaphor sentences are maintained in the target language (TL).Keywords : Metaphor, Translation Strategies, Maintain Metaphor

The Translation Problem Types in Translating Indonesia Text to English (A Case Study of Translation Subject of Fifth Semester English Students –UPY)

2020 ◽  
Vol 4 (1) ◽  
Author(s):  
Sujatmiko Sujatmiko
Keyword(s):  
Qualitative Method ◽  
English Department ◽  
Problem Types ◽  
Translation Technique ◽  
Data Source ◽  
Word Translation ◽  
Translation Accuracy ◽  
English Students ◽  
Successful Transfer

This research is entitled “The Translation Problem Types in Translating Indonesia textinto English (A Case Study of Translation Subject of Fifth Semester English Department –UPY) . It is about how Indonesia text is translated into English by English students, toidentify the translation problems, and to identify the problematics of translation technique.This research uses qualitative method to analyze the data. Techniques of analyzing datain this research consist of 3 components, they are (1) reducing the data, (2) explaining thedata, and (3) taking a conclusion. Reducing data is a process of selecting, focusing,simplifying and abstracting the data. Explaining the data is a process of organizinginformation and arranging the complete narration. Taking a conclusion is a process ofdrawing conclusion from the data. The data source of this research are Indonesia text andstudent’s translation.After conducting the research, the research find the data that all respondents havesimilar translation problem types in translating Indonesia text into English. The problems arediction, tenses, no equivalence translation; others have problems of adverb, article, andrelative clause. None of respondents apply other translation technique. They only apply wordper word translation technique. The accuracy of transfer level is adequate level. Only onerespondent have almost completely successful transfer level. Other respondents haveadequate accuracy transfer level. By applying the untrue translation technique has an impactto translation accuracy transfer level.This research is expected to open wide opportunities and challenges to academicians,especially those in translation linguistics sphere to deepen their research and study, especiallyin translating Indonesia text to English in order to be a new contribution to the translationfields.

Explorations of Cohen, Dunbar, and McClelland's (1990) connectionist model of Stroop performance.

1998 ◽  
Vol 105 (1) ◽  
pp. 174-187 ◽  
Author(s):  
Stephen M. Kanne ◽  
David A. Balota ◽  
Daniel H. Spieler ◽  
Mark E. Faust
Keyword(s):  
Connectionist Model
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