Open Science Research Excellence

Open Science Index

Commenced in January 2007 Frequency: Monthly Edition: International Paper Count: 13

13
10010160
Machine Translation Analysis of Chinese Dish Names
Abstract:
This article presents a comparative study evaluating and comparing the quality of machine translation (MT) output of Chinese gastronomy nomenclature. Chinese gastronomic culture is experiencing an increased international acknowledgment nowadays. The nomenclature of Chinese gastronomy not only reflects a specific aspect of culture, but it is related to other areas of society such as philosophy, traditional medicine, etc. Chinese dish names are composed of several types of cultural references, such as ingredients, colors, flavors, culinary techniques, cooking utensils, toponyms, anthroponyms, metaphors, historical tales, among others. These cultural references act as one of the biggest difficulties in translation, in which the use of translation techniques is usually required. Regarding the lack of Chinese food-related translation studies, especially in Chinese-Spanish translation, and the current massive use of MT, the quality of the MT output of Chinese dish names is questioned. Fifty Chinese dish names with different types of cultural components were selected in order to complete this study. First, all of these dish names were translated by three different MT tools (Google Translate, Baidu Translate and Bing Translator). Second, a questionnaire was designed and completed by 12 Chinese online users (Chinese graduates of a Hispanic Philology major) in order to find out user preferences regarding the collected MT output. Finally, human translation techniques were observed and analyzed to identify what translation techniques would be observed more often in the preferred MT proposals. The result reveals that the MT output of the Chinese gastronomy nomenclature is not of high quality. It would be recommended not to trust the MT in occasions like restaurant menus, TV culinary shows, etc. However, the MT output could be used as an aid for tourists to have a general idea of a dish (the main ingredients, for example). Literal translation turned out to be the most observed technique, followed by borrowing, generalization and adaptation, while amplification, particularization and transposition were infrequently observed. Possibly because that the MT engines at present are limited to relate equivalent terms and offer literal translations without taking into account the whole context meaning of the dish name, which is essential to the application of those less observed techniques. This could give insight into the post-editing of the Chinese dish name translation. By observing and analyzing translation techniques in the proposals of the machine translators, the post-editors could better decide which techniques to apply in each case so as to correct mistakes and improve the quality of the translation.
12
10006362
Knowledge Required for Avoiding Lexical Errors at Machine Translation
Abstract:
This research aims at finding out the causes that led to wrong lexical selections in machine translation (MT) rather than categorizing lexical errors, which has been a main practice in error analysis. By manually examining and analyzing lexical errors outputted by a MT system, it suggests what knowledge would help the system reduce lexical errors.
11
10006612
Study of Syntactic Errors for Deep Parsing at Machine Translation
Abstract:

Syntactic parsing is vital for semantic treatment by many applications related to natural language processing (NLP), because form and content coincide in many cases. However, it has not yet reached the levels of reliable performance. By manually examining and analyzing individual machine translation output errors that involve syntax as well as semantics, this study attempts to discover what is required for improving syntactic and semantic parsing.

10
10006107
Contextual Distribution for Textual Alignment
Abstract:

Our program compares French and Italian translations of Homer’s Odyssey, from the XVIth to the XXth century. We focus on the third point, showing how distributional semantics systems can be used both to improve alignment between different French translations as well as between the Greek text and a French translation. Although we focus on French examples, the techniques we display are completely language independent.

9
10000946
Perception and Implementation of Machine Translation Applications by the Iranian English Translators
Abstract:

The present study is an attempt to provide a relatively comprehensive preview of the Iranian English translators’ perception on Machine Translation. Furthermore, the study tries to shed light on the status of implementation of Machine Translation among the Iranian English Translators. To reach the aforementioned objectives, the Localization Industry Standards Association’s questioner for measuring perceptions with regard to the adoption of a technology innovation was adapted and used to investigate the perception and implementation of Machine Translation applications by the Iranian English language translators. The participants of the study were 224 last-year undergraduate Iranian students of English translation at 10 universities across the country. The study revealed a very low level of adoption and a very high level of willingness to get familiar with and learn about Machine Translation, as well as a positive perception of and attitude toward Machine Translation by the Iranian English translators.

8
9999654
Combined Automatic Speech Recognition and Machine Translation in Business Correspondence Domain for English-Croatian
Abstract:

The paper presents combined automatic speech recognition (ASR) of English and machine translation (MT) for English and Croatian and Croatian-English language pairs in the domain of business correspondence. The first part presents results of training the ASR commercial system on English data sets, enriched by error analysis. The second part presents results of machine translation performed by free online tool for English and Croatian and Croatian-English language pairs. Human evaluation in terms of usability is conducted and internal consistency calculated by Cronbach's alpha coefficient, enriched by error analysis. Automatic evaluation is performed by WER (Word Error Rate) and PER (Position-independent word Error Rate) metrics, followed by investigation of Pearson’s correlation with human evaluation.

7
15130
A Thai to English Machine Translation System Using Thai LFG Tree Structure as Interlingua
Abstract:

Machine Translation (MT) between the Thai and English languages has been a challenging research topic in natural language processing. Most research has been done on English to Thai machine translation, but not the other way around. This paper presents a Thai to English Machine Translation System that translates a Thai sentence into interlingua of a Thai LFG tree using LFG grammar and a bottom up parser. The Thai LFG tree is then transformed into the corresponding English LFG tree by pattern matching and node transformation. Finally, an equivalent English sentence is created using structural information prescribed by the English LFG tree. Based on results of experiments designed to evaluate the performance of the proposed system, it can be stated that the system has been proven to be effective in providing a useful translation from Thai to English.

6
4467
Performance Analysis of MT Evaluation Measures and Test Suites
Abstract:
Many measures have been proposed for machine translation evaluation (MTE) while little research has been done on the performance of MTE methods. This paper is an effort for MTE performance analysis. A general frame is proposed for the description of the MTE measure and the test suite, including whether the automatic measure is consistent with human evaluation, whether different results from various measures or test suites are consistent, whether the content of the test suite is suitable for performance evaluation, the degree of difficulty of the test suite and its influence on the MTE, the relationship of MTE result significance and the size of the test suite, etc. For a better clarification of the frame, several experiment results are analyzed relating human evaluation, BLEU evaluation, and typological MTE. A visualization method is introduced for better presentation of the results. The study aims for aid in construction of test suite and method selection in MTE practice.
5
10738
Estimating Word Translation Probabilities for Thai – English Machine Translation using EM Algorithm
Abstract:
Selecting the word translation from a set of target language words, one that conveys the correct sense of source word and makes more fluent target language output, is one of core problems in machine translation. In this paper we compare the 3 methods of estimating word translation probabilities for selecting the translation word in Thai – English Machine Translation. The 3 methods are (1) Method based on frequency of word translation, (2) Method based on collocation of word translation, and (3) Method based on Expectation Maximization (EM) algorithm. For evaluation we used Thai – English parallel sentences generated by NECTEC. The method based on EM algorithm is the best method in comparison to the other methods and gives the satisfying results.
4
9331
Extracting Multiword Expressions in Machine Translation from English to Urdu using Relational Data Approach
Abstract:
Machine Translation, (hereafter in this document referred to as the "MT") faces a lot of complex problems from its origination. Extracting multiword expressions is also one of the complex problems in MT. Finding multiword expressions during translating a sentence from English into Urdu, through existing solutions, takes a lot of time and occupies system resources. We have designed a simple relational data approach, in which we simply set a bit in dictionary (database) for multiword, to find and handle multiword expression. This approach handles multiword efficiently.
3
3423
AGHAZ : An Expert System Based approach for the Translation of English to Urdu
Abstract:

Machine Translation (MT 3) of English text to its Urdu equivalent is a difficult challenge. Lot of attempts has been made, but a few limited solutions are provided till now. We present a direct approach, using an expert system to translate English text into its equivalent Urdu, using The Unicode Standard, Version 4.0 (ISBN 0-321-18578-1) Range: 0600–06FF. The expert system works with a knowledge base that contains grammatical patterns of English and Urdu, as well as a tense and gender-aware dictionary of Urdu words (with their English equivalents).

2
4171
Continuous Text Translation Using Text Modeling in the Thetos System
Abstract:
In the paper a method of modeling text for Polish is discussed. The method is aimed at transforming continuous input text into a text consisting of sentences in so called canonical form, whose characteristic is, among others, a complete structure as well as no anaphora or ellipses. The transformation is lossless as to the content of text being transformed. The modeling method has been worked out for the needs of the Thetos system, which translates Polish written texts into the Polish sign language. We believe that the method can be also used in various applications that deal with the natural language, e.g. in a text summary generator for Polish.
1
5867
Determining the Gender of Korean Names for Pronoun Generation
Abstract:
It is an important task in Korean-English machine translation to classify the gender of names correctly. When a sentence is composed of two or more clauses and only one subject is given as a proper noun, it is important to find the gender of the proper noun for correct translation of the sentence. This is because a singular pronoun has a gender in English while it does not in Korean. Thus, in Korean-English machine translation, the gender of a proper noun should be determined. More generally, this task can be expanded into the classification of the general Korean names. This paper proposes a statistical method for this problem. By considering a name as just a sequence of syllables, it is possible to get a statistics for each name from a collection of names. An evaluation of the proposed method yields the improvement in accuracy over the simple looking-up of the collection. While the accuracy of the looking-up method is 64.11%, that of the proposed method is 81.49%. This implies that the proposed method is more plausible for the gender classification of the Korean names.
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