scholarly journals Interpretation and machine translation towards google translate as a part of machine translation and teaching translation

2021 ◽  
Author(s):  
Vichard L. Kane
Keyword(s):  
Machine Translation ◽  
Language Comprehension ◽  
Computer Interpretation ◽  
Real Importance ◽  
The One

Language comprehension is the capacity of someone to properly understand the language to fully communicate the message and details. When dialects are distinct, the problem arises. This condition can lead to misconception as understudies, particularly those whose specialty is not English, cannot gain real importance. Along these lines, interpreting is regarded as one of the suggested arrangements in this area. As the results, the message's basic significance and setting in an unknown dialect can be precisely seen in English. Interpretation is a help to resolve this language boundary for this case. Moreover, finding an individual who is accessible to decipher each and every language is found troublesome. Furthermore, the aftereffect of interpretation is by one way or another influenced and impacted by the interpreter's abilities. In this manner, interpretation application turns into the one to be depended on. A lot of online interpretation applications have been made available for the last few years. The best one is Google Translate which is a multi-lingual online computer interpretation (MT) system. It is said as a multilanguage interpretation programme, as it can decode material from over 90 dialects.

Events Reconsidered

2003 ◽  
Author(s):  
J. S. Weiner ◽  
Chris Stringer
Keyword(s):  
Scientific Literature ◽  
British Museum ◽  
Primary Sources ◽  
The Public ◽  
Public Meeting ◽  
Real Importance ◽  
New Form ◽  
To Come ◽  
The One ◽  
Work Done

It is unfortunately not possible to follow in any detail every stage of Smith Woodward’s activities at Piltdown. No diaries or note-books exist of the work done, there is nowhere a complete record of the various finds as they were made. Woodward kept copies of very few of his own letters and we have only the letters written to him and now preserved at the British Museum. When the American palaeontologist Osborn came over in 1920, Woodward dictated some notes which help to allocate the various discoveries. Apart from these notes and the one-sided record of the correspondence, there are only the reports in the scientific literature and popular lectures on Piltdown as primary sources. Woodward does not appear in general to have been a secretive man, but over the Piltdown material he went to some lengths to keep the whole affair as quiet as possible until near the time of the public meeting in December 1912. He did not consult any of his colleagues in the Museum about the finds or about the interpretation he was to place on them. Mr. Hinton says that to his colleagues at South Kensington Woodward’s diagnosis of E. dawsoni came as a surprise mingled with some dismay, for there was much scepticism of the new form amongst his museum colleagues, including Oldfield Thomas and Hinton himself. They would have advised caution, he says. Keith knew nothing of the events in Sussex until rumours reached him in November. He wrote asking for a view of the exciting material, but on his visit on 2 December to the Museum he was received rather coldly and allowed a short twenty minutes. But, judging from Dawson’s letters in 1912, it seems fair to say that Woodward was merely seeking to avoid a premature disclosure, for he had decided early on that Piltdown would indeed prove a sensational event. Woodward did not want any of Dawson’s ‘lay’ friends to come along on his first visit to the gravel when he had yet to make up his mind about the real importance of Dawson’s find and of the necessity for systematic excavation.

Estimating Machine Translation Quality of Any Input Sentence

2020 ◽  
Vol 30 (01) ◽  
pp. 2050002
Author(s):  
Taichi Aida ◽  
Kazuhide Yamamoto
Keyword(s):  
Machine Translation ◽  
Evaluation Model ◽  
Joint Probability ◽  
Translation System ◽  
Neural Machine Translation ◽  
Translation Quality ◽  
Machine Translation System ◽  
Input Sentence ◽  
The One

Current methods of neural machine translation may generate sentences with different levels of quality. Methods for automatically evaluating translation output from machine translation can be broadly classified into two types: a method that uses human post-edited translations for training an evaluation model, and a method that uses a reference translation that is the correct answer during evaluation. On the one hand, it is difficult to prepare post-edited translations because it is necessary to tag each word in comparison with the original translated sentences. On the other hand, users who actually employ the machine translation system do not have a correct reference translation. Therefore, we propose a method that trains the evaluation model without using human post-edited sentences and in the test set, estimates the quality of output sentences without using reference translations. We define some indices and predict the quality of translations with a regression model. For the quality of the translated sentences, we employ the BLEU score calculated from the number of word [Formula: see text]-gram matches between the translated sentence and the reference translation. After that, we compute the correlation between quality scores predicted by our method and BLEU actually computed from references. According to the experimental results, the correlation with BLEU is the highest when XGBoost uses all the indices. Moreover, looking at each index, we find that the sentence log-likelihood and the model uncertainty, which are based on the joint probability of generating the translated sentence, are important in BLEU estimation.

scholarly journals Experts, Errors, and Context: A Large-Scale Study of Human Evaluation for Machine Translation

2021 ◽  
Vol 9 ◽  
pp. 1460-1474
Author(s):  
Markus Freitag ◽  
George Foster ◽  
David Grangier ◽  
Viresh Ratnakar ◽  
Qijun Tan ◽  
...  
Keyword(s):  
Machine Translation ◽  
Large Scale ◽  
Standard Procedure ◽  
Difficult Problem ◽  
Evaluation Methodology ◽  
Evaluation Procedures ◽  
Human Evaluation ◽  
The One ◽  
Human Crowd ◽  
Translation Systems

Abstract Human evaluation of modern high-quality machine translation systems is a difficult problem, and there is increasing evidence that inadequate evaluation procedures can lead to erroneous conclusions. While there has been considerable research on human evaluation, the field still lacks a commonly accepted standard procedure. As a step toward this goal, we propose an evaluation methodology grounded in explicit error analysis, based on the Multidimensional Quality Metrics (MQM) framework. We carry out the largest MQM research study to date, scoring the outputs of top systems from the WMT 2020 shared task in two language pairs using annotations provided by professional translators with access to full document context. We analyze the resulting data extensively, finding among other results a substantially different ranking of evaluated systems from the one established by the WMT crowd workers, exhibiting a clear preference for human over machine output. Surprisingly, we also find that automatic metrics based on pre-trained embeddings can outperform human crowd workers. We make our corpus publicly available for further research.

scholarly journals RankEval: Open Tool for Evaluation of Machine-Learned Ranking

2013 ◽  
Vol 100 (1) ◽  
pp. 63-72 ◽  
Author(s):  
Eleftherios Avramidis
Keyword(s):  
Information Retrieval ◽  
Open Source ◽  
Machine Translation ◽  
Research Field ◽  
Reward Systems ◽  
Quality Estimation ◽  
Open Source Tool ◽  
Statistical Measures ◽  
The One ◽  
Reciprocal Rank

Abstract Recent research and applications for evaluation and quality estimation of Machine Translation require statistical measures for comparing machine-predicted ranking against gold sets annotated by humans. Additional to the existing practice of measuring segment-level correlation with Kendall tau, we propose using ranking metrics from the research field of Information Retrieval such as Mean Reciprocal Rank, Normalized Discounted Cumulative Gain and Expected Reciprocal Rank. These reward systems that predict correctly the highest ranked items than the one of lower ones. We present an open source tool ”RANKEVAL” providing implementation of these metrics. It can be either run independently as a script supporting common formats or can be imported to any Python application.

scholarly journals COSTA MT Evaluation Tool: An Open Toolkit for Human Machine Translation Evaluation

2013 ◽  
Vol 100 (1) ◽  
pp. 83-89 ◽  
Author(s):  
Konstantinos Chatzitheodorou
Keyword(s):  
Machine Translation ◽  
Evaluation Tool ◽  
Machine Translation Evaluation ◽  
Translation Error ◽  
Mt Evaluation ◽  
Java Program ◽  
Error Classification ◽  
The One ◽  
Language Pair

Abstract A hotly debated topic in machine translation is human evaluation. On the one hand, it is extremely costly and time consuming; on the other, it is an important and unfortunately inevitable part of any system. This paper describes COSTA MT Evaluation Tool, an open stand-alone tool for human machine translation evaluation. It is a Java program that can be used to manually evaluate the quality of the machine translation output. It is simple in use, designed to allow machine translation potential users and developers to analyze their systems using a friendly environment. It enables the ranking of the quality of machine translation output segment-bysegment for a particular language pair. The benefits of this tool are multiple. Firstly, it is a rich repository of commonly used industry criteria (fluency, adequacy and translation error classification). Secondly, it is freely available to anyone and provides results that can be further analyzed. Thirdly, it estimates the time needed for each evaluated sentence. Finally, it gives suggestions about the fuzzy matching of the candidate translations.

scholarly journals A Linguistic Evaluation of Rule-Based, Phrase-Based, and Neural MT Engines

2017 ◽  
Vol 108 (1) ◽  
pp. 159-170 ◽  
Author(s):  
Aljoscha Burchardt ◽  
Vivien Macketanz ◽  
Jon Dehdari ◽  
Georg Heigold ◽  
Jan-Thorsten Peter ◽  
...  
Keyword(s):  
Machine Translation ◽  
Large Range ◽  
The Other ◽  
Test Suite ◽  
Rule Based ◽  
Online System ◽  
Other Hand ◽  
The One

AbstractIn this paper, we report an analysis of the strengths and weaknesses of several Machine Translation (MT) engines implementing the three most widely used paradigms. The analysis is based on a manually built test suite that comprises a large range of linguistic phenomena. Two main observations are on the one hand the striking improvement of an commercial online system when turning from a phrase-based to a neural engine and on the other hand that the successful translations of neural MT systems sometimes bear resemblance with the translations of a rule-based MT system.

scholarly journals Evaluating the effectiveness of machine translation of audio description: the results of two pilot studies in the English-Dutch language pair

2021 ◽  
pp. 226-252
Author(s):  
Gert Vercauteren ◽  
Nina Reviers ◽  
Kim Steyaert
Keyword(s):  
Machine Translation ◽  
New Technologies ◽  
Pilot Studies ◽  
Audio Description ◽  
Sight Loss ◽  
Dutch Language ◽  
The One ◽  
Concrete Language ◽  
Constant Improvement ◽  
Language Pair

The field of translation is undergoing various profound changes. On the one hand it is being thoroughly reshaped by the advent and constant improvement of new technologies. On the other hand, new forms of translation are starting to see the light of day in the wake of social and legal developments that require that products and content that are created, are accessible for everybody. One of these new forms of translation, is audio description (AD), a service that is aimed at making audiovisual content accessible to people with sight loss. New legislation requires that this content is accessible by 2025, which constitutes a tremendous task given the limited number of people that are at present trained as audio describers. A possible solution would be to use machine translation to translate existing audio descriptions into different languages. Since AD is characterized by short sentences and simple, concrete language, it could be a good candidate for machine translation. In the present study, we want to test this hypothesis for the English-Dutch language pair. Three 30 minute AD excerpts of different Dutch movies that were originally audio described in English, were translated into Dutch using DeepL. The translations were analysed using the harmonized DQF-MQM error typology and taking into account the specific multimodal nature of the source text and the intersemiotic dimension of the original audio description process. The analysis showed that the MT output had a relatively high error rate, particularly in the categories of Accuracy – mistranslation and Fluency – grammar. This seems to indicate that extensive post-editing will be needed, before the text can be used in a professional context.

Word Sense Based Hindi-Tamil Statistical Machine Translation

2020 ◽  
pp. 410-421
Author(s):  
Vimal Kumar K. ◽  
Divakar Yadav
Keyword(s):  
Machine Translation ◽  
Language Processing ◽  
Semantic Analysis ◽  
Translation System ◽  
Great Success ◽  
Source Language ◽  
Additional Information ◽  
Part Of Speech ◽  
Preceding Word ◽  
The One

Corpus based natural language processing has emerged with great success in recent years. It is not only used for languages like English, French, Spanish, and Hindi but also is widely used for languages like Tamil, Telugu etc. This paper focuses to increase the accuracy of machine translation from Hindi to Tamil by considering the word's sense as well as its part-of-speech. This system works on word by word translation from Hindi to Tamil language which makes use of additional information such as the preceding words, the current word's part of speech and the word's sense itself. For such a translation system, the frequency of words occurring in the corpus, the tagging of the input words and the probability of the preceding word of the tagged words are required. Wordnet is used to identify various synonym for the words specified in the source language. Among these words, the one which is more relevant to the word specified in source language is considered for the translation to target language. The introduction of the additional information such as part-of-speech tag, preceding word information and semantic analysis has greatly improved the accuracy of the system.

scholarly journals Machine translation quality in an audiovisual context

Target ◽  
2016 ◽  
Vol 28 (2) ◽  
pp. 206-221 ◽  
Author(s):  
Aljoscha Burchardt ◽  
Arle Lommel ◽  
Lindsay Bywood ◽  
Kim Harris ◽  
Maja Popović
Keyword(s):  
Machine Translation ◽  
The Other ◽  
High Quality ◽  
Innovative Technologies ◽  
Translation Quality ◽  
The World ◽  
The Future ◽  
Audiovisual Translation ◽  
Ultimate Objective ◽  
The One

Abstract The volume of Audiovisual Translation (AVT) is increasing to meet the rising demand for data that needs to be accessible around the world. Machine Translation (MT) is one of the most innovative technologies to be deployed in the field of translation, but it is still too early to predict how it can support the creativity and productivity of professional translators in the future. Currently, MT is more widely used in (non-AV) text translation than in AVT. In this article, we discuss MT technology and demonstrate why its use in AVT scenarios is particularly challenging. We also present some potentially useful methods and tools for measuring MT quality that have been developed primarily for text translation. The ultimate objective is to bridge the gap between the tech-savvy AVT community, on the one hand, and researchers and developers in the field of high-quality MT, on the other.

scholarly journals Lexical norms, language comprehension, and the epistemology of testimony

2014 ◽  
Vol 44 (3-4) ◽  
pp. 324-342 ◽  
Author(s):  
Endre Begby
Keyword(s):  
Language Comprehension ◽  
The Other ◽  
Collective Effort ◽  
Tyler Burge ◽  
Lexical Norms ◽  
Epistemology Of Testimony ◽  
The One

It has recently been argued (for instance by Sanford Goldberg, expanding on earlier work by Tyler Burge) that public linguistic norms are implicated in the epistemology of testimony by way of underwriting the reliability of language comprehension. This paper argues that linguistic normativity, as such, makes no explanatory contribution to the epistemology of testimony, but instead emerges naturally out of a collective effort to maintain language as a reliable medium for the dissemination of knowledge. Consequently, the epistemologies of testimony and language comprehension are deeply intertwined from the start, and there is no room for grounding the one in terms of the other.

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