An Analisys Of English-Indonesian Translation Of The Film’s Sub-Titling Friends

This research is entitled: An Analysis of English Indonesian Translation of the Film’s Sub-Titling Friends. It is a descriptive study on the development of the language translation, especially in film. Started from the theory that the knowledge translation is reproducing the source language into receptor language in order to delivery the massage. These research studies the phenomena of deviant translation happened in the film sub-titling Friends in the episode “The Halloween Party”. Focused on the deviation of translation, this research was to find the numbers of deviation and the factors that may affect the translation to deviate from its original script. Finally, the writer is able to identify the level of appropriateness of the data that is used. Descriptive method was used here, and total sampling technique was employed. Data were taken from the Indonesian translated scrip t of film Friends in the episode of “The Halloween Party” and its original script in English. Data collecting was done by watching the film repeatedly to collect translation deviations in the dialogues (including within it are inappropriate translation and the untranslated words, phrases, clauses, and sentences). The base for judging deviations is the inappropriate translation and the untranslated words, phrases, clauses, and sentences, with exceptions of the use of reduction text. Coding the data according to the determined rules, and then classifying them to the previously determined classifications did the data analyzing. The study shows that there are 314 data in this film, 23 of which indicate the translation deviations. They consist of classification codes A 7 numbers of data of the inappropriate translations and classification codes B 16 numbers of data of the untranslated words, phrases, clauses, and sentences. The translation of the film Friends in the episode “The Halloween Party” is satisfactory considering that less than half of the data indicates translation deviation. This translation is placed in good level of appropriateness considering that its sub-titles is fully observe the type of program, the target of the audience, and the aesthetics of the language. The researcher hopefully that this research will be useful in adding the about film translation. The extra-linguistics elements of a film are very important to consider beside the dialogue itself

Integrating E-Books into the Collection: Some Practical Considerations

About five years ago, when many believed digitization would become the panacea for libraries, some of our colleagues predicted that e-books would supplant print. For example, Andrew Pace wrote in 2000: “In five years e-book sales will match those of traditional print; in ten years, e-books will outsell print. There is little doubt left in my mind – e-books are among us and are here to stay.”1 While the proliferation of e-books has not matched the lofty predictions, the availability and usability of e-books is expanding each year. The options for reader and search platforms have increased, more titles are becoming available, prices have stabilized, and selection options have evolved. Library information infrastructure has likewise matured. Remote access by proxy authentication is more widespread than five years ago; some libraries are part of a wireless network enabling students to conduct distributed research; and online distance education is burgeoning. E-books are finally a reasonable option for supplementing the library collection. This paper will provide a short primer on cataloging and access for librarians who are planning to add e-books. While several platforms for e-books exist (such as a digital book on a CD-ROM or a digitized book that the library itself has created), this paper will limit the discussion to the prevalent platform model: a vendor-supplied, web-accessible content, such as NetLibary

Synthetic Data and Artificial Neural Networks for Natural Scene Text Recognition

In this work we present a framework for the recognition of natural scene text. Our framework does not require any human-labelled data, and performs word recognition on the whole image holistically, departing from the character based recognition systems of the past. The deep neural network models at the centre of this framework are trained solely on data produced by a synthetic text generation engine -- synthetic data that is highly realistic and sufficient to replace real data, giving us infinite amounts of training data. This excess of data exposes new possibilities for word recognition models, and here we consider three models, each one "reading" words in a different way: via 90k-way dictionary encoding, character sequence encoding, and bag-of-N-grams encoding. In the scenarios of language based and completely unconstrained text recognition we greatly improve upon state-of-the-art performance on standard datasets, using our fast, simple machinery and requiring zero data-acquisition costs

More blogging features for author identification

In this paper we present a novel improvement in the field of authorship identification in personal blogs. The improvement in authorship identification, in our work, is by utilizing a hybrid collection of linguistic features that best capture the style of users in diaries blogs. The features sets contain LIWC with its psychology background, a collection of syntactic features & part-of-speech (POS), and the misspelling errors features. Furthermore, we analyze the contribution of each feature set on the final result and compare the outcome of using different combination from the selected feature sets. Our new categorization of misspelling words which are mapped into numerical features, are noticeably enhancing the classification results. The paper also confirms the best ranges of several parameters that affect the final result of authorship identification such as the author numbers, words number in each post, and the number of documents/posts for each author/user. The results and evaluation show that the utilized features are compact, while their performance is highly comparable with other much larger feature sets

Weighted-Sampling Audio Adversarial Example Attack

Recent studies have highlighted audio adversarial examples as a ubiquitous threat to state-of-the-art automatic speech recognition systems. Thorough studies on how to effectively generate adversarial examples are essential to prevent potential attacks. Despite many research on this, the efficiency and the robustness of existing works are not yet satisfactory. In this paper, we propose~\textit{weighted-sampling audio adversarial examples}, focusing on the numbers and the weights of distortion to reinforce the attack. Further, we apply a denoising method in the loss function to make the adversarial attack more imperceptible. Experiments show that our method is the first in the field to generate audio adversarial examples with low noise and high audio robustness at the minute time-consuming level.Comment: https://aaai.org/Papers/AAAI/2020GB/AAAI-LiuXL.9260.pd

HELIN Cataloging Policies and Procedures Manual

HELIN Cataloging Manual - Nov. 2011 revisio