Subtitling, one of the under-researched topics in translation studies, is a challenging task faced by many restrictions that compel subtitlers to use specific strategies to enhance the quality of the subtitles. In relation to this, this study aimed to identify the subtitling strategies adopted in subtitling the culture-bound terms in the American movie entitled ‘The American Pie’, and to assess the quality of the translation of these terms. For this purpose, the data was collected from the movie and qualitatively analyzed using Pedersen's (2005, 2011) typology and Pedersen's (2017) quality assessment model. The results of the study showed that most of the strategies proposed by Pedersen were used. It was also found that some other translation strategies were used in the subtitles. Two new subtitling strategies were identified by the author, viz., using euphemistic expressions and using formal language to render informal language. The quality assessment showed that most subtitles are of a good quality, as in few cases there were some serious errors or problems.

Semantic loss, which refers to over-, under-, or mistranslation of a source text (ST), may result in partial or complete loss of meaning in the target text (TT). This phenomenon is prevalent in the translations of an ST, especially translations of the Holy Qur'an due to factors such as the lack of equivalence of some cultural words in the target language (TL). In relation to this, translators of this holy book have been critiqued for their inability to completely convey the true and accurate meanings of the Holy Qur'an. This study attempted to investigate the semantic loss in the translation of the Surah al-WaqiAAa by Abdullah Yusuf Ali. It also examined the frequency and causes of such losses. This research, which is qualitative in nature, utilized descriptive content analysis of the Surah. The translation of the ayat [verses] related to the problem of the research has been extracted from the work of Abdullah Yusuf Ali, The Holy Qur'an: Text and Translation. The meanings of the translated verses were verified by two Arabic language experts who had mastered English as well. The causes of losses were identified according to Baker's typology. The findings showed frequent partial and complete semantic loss of meanings mostly due to mistranslations, semantic complexity of the vocabularies, and culture.

Translating the Holy Quran is a challenging task. However, it is a necessity due to the large number of Muslims who do not speak Arabic. To date, various translations are available for nonnative speakers of Arabic. These translations, however, have revealed complete and partial translation losses. One type of such losses is grammatical loss, which sometimes occurs due to differences between the source text (ST) and the target text (TT). This study aimed at investigating the grammatical losses in the translation of the Holy Quran, with special reference to Surah Al A’araf, and the extent these losses cause partial or complete semantic loss. Qualitative descriptive approach was adopted to analyze the data extracted from Abdel Haleem’s English translation of Surah Al A’araf. The study revealed losses occurring in translating grammatical aspects such as conjunctions, syntactic order, duality, tense, and verbs. It was also found that grammatical losses contributed to semantic losses, which are mostly partial semantic losses of the connotative or the expressive meanings. However, some of the identified grammatical losses were found to cause complete semantic losses. This study suggests that appropriate translation strategies be adopted to reduce loss in the translation.

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This study aims at identifying the common types of errors in Google Translate (GT) in the translation of informative news texts from Arabic to English, to measure the translation errors quality and to assess the fluency and the semantic adequacy of the translation output, and therefore to explain the extent a human translator is needed to rectify the output translation. For this purpose, some examples were purposively selected from online newspapers. The collected data was analyzed using a mixed method approach, as the errors were qualitatively identified, guided by Hsu’s (2014) classification of machine translation errors. Quantitative descriptive approach was used to measure the translation errors quality, using the Multidimensional Quality Metrics and Localization Quality Evaluation. As for assessing the semantic adequacy and fluency, a questionnaire that was adapted from Dorr, Snover, and Madnani (2011) was used. The results of the analysis show that omission, which is a lexical error and inappropriate lexical choice, which is a semantic error are the most common errors. Inappropriate lexical choice is sometimes a result of the homophonic nature of some source text words which can be misinterpreted by the machine translation system. This study concludes that it is useful to use machine translation systems to expedite the translation process, but that accuracy is sacrificed for the sake of ease (less work for the human) and speed of translation. If greater accuracy is required, or desired, a human translator must at least proofread and work on the material.