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Voluntary sector advice agencies have performed an important function in providing free, accessible advice in the UK for many decades. As legal aid is slashed, and 'austerity' leaves everyday life for many ever more precarious, their role has never been more essential. Advice agencies provide a dynamic and increasingly significant transition point where the rights, responsibilities and grievances of the individual are brought into dialogue with formal legal structures. Drawing on ideas from the 'sociology of translation', this paper sets out to consider the multiple, complex roles these organizations play. They are involved not simply in the delivery of advice to individuals, but in a collective concern that translates personal grievances into matters-of- public-concern. The paper concludes by considering the implications for an emerging research agenda that considers advice organizations as legal actors in a fragmenting world.

During my Ph.D. study, I conducted research in Machine Translation (MT), i.e. finding a possible target translation of a source sentence without any human interference. My works focused on statistical approach of MT which consists in using different probabilistic models trained on large amount of parallel corpora to retrieve the most likelihood translation given a source sentence. My thesis addresses two issues related to Statistical Machine Translation (SMT) : the collect of aligned parallel corpora and the estimation of translation models given these corpora. An SMT system extracts the knowledge necessary to perform automatic translation from parallel corpora where each source sentence is aligned with its translation in a target language. Most researches dealing with SMT use as parallel corpora the proceedings of the European Parliament available in many languages. Such corpora are not convenient for spontaneous speech translation. That's why I decided to use movie subtitles in order to achieve a more realistic machine translation system. Movie subtitles are considered as difficult data and cannot be used as parallel corpora for SMT without processing. I proposed an original algorithm based on Dynamic Time Wrapping to automatically align movie subtitles. Thus, I obtained parallel corpora that constitute a rich resource to train SMT system. In SMT, different statistical models are trained on parallel corpora such as alignment model, translation table, or distortion model. The translation table is the major model needed by an SMT system to perform the process. It gives the translation probability between target and source words. Existing methods usually estimate these tables based on word alignment which is obtained through complex and thus time consuming algorithms. My principal purpose was to rethink the problem and to prospect new options for generating the translation tables, at word and phrase level, which are totally different from state-of-the-art solutions. I proposed an original approach based on ...

During my Ph.D. study, I conducted research in Machine Translation (MT), i.e. finding a possible target translation of a source sentence without any human interference. My works focused on statistical approach of MT which consists in using different probabilistic models trained on large amount of parallel corpora to retrieve the most likelihood translation given a source sentence. My thesis addresses two issues related to Statistical Machine Translation (SMT) : the collect of aligned parallel corpora and the estimation of translation models given these corpora. An SMT system extracts the knowledge necessary to perform automatic translation from parallel corpora where each source sentence is aligned with its translation in a target language. Most researches dealing with SMT use as parallel corpora the proceedings of the European Parliament available in many languages. Such corpora are not convenient for spontaneous speech translation. That's why I decided to use movie subtitles in order to achieve a more realistic machine translation system. Movie subtitles are considered as difficult data and cannot be used as parallel corpora for SMT without processing. I proposed an original algorithm based on Dynamic Time Wrapping to automatically align movie subtitles. Thus, I obtained parallel corpora that constitute a rich resource to train SMT system. In SMT, different statistical models are trained on parallel corpora such as alignment model, translation table, or distortion model. The translation table is the major model needed by an SMT system to perform the process. It gives the translation probability between target and source words. Existing methods usually estimate these tables based on word alignment which is obtained through complex and thus time consuming algorithms. My principal purpose was to rethink the problem and to prospect new options for generating the translation tables, at word and phrase level, which are totally different from state-of-the-art solutions. I proposed an original approach based on ...

During my Ph.D. study, I conducted research in Machine Translation (MT), i.e. finding a possible target translation of a source sentence without any human interference. My works focused on statistical approach of MT which consists in using different probabilistic models trained on large amount of parallel corpora to retrieve the most likelihood translation given a source sentence. My thesis addresses two issues related to Statistical Machine Translation (SMT) : the collect of aligned parallel corpora and the estimation of translation models given these corpora. An SMT system extracts the knowledge necessary to perform automatic translation from parallel corpora where each source sentence is aligned with its translation in a target language. Most researches dealing with SMT use as parallel corpora the proceedings of the European Parliament available in many languages. Such corpora are not convenient for spontaneous speech translation. That's why I decided to use movie subtitles in order to achieve a more realistic machine translation system. Movie subtitles are considered as difficult data and cannot be used as parallel corpora for SMT without processing. I proposed an original algorithm based on Dynamic Time Wrapping to automatically align movie subtitles. Thus, I obtained parallel corpora that constitute a rich resource to train SMT system. In SMT, different statistical models are trained on parallel corpora such as alignment model, translation table, or distortion model. The translation table is the major model needed by an SMT system to perform the process. It gives the translation probability between target and source words. Existing methods usually estimate these tables based on word alignment which is obtained through complex and thus time consuming algorithms. My principal purpose was to rethink the problem and to prospect new options for generating the translation tables, at word and phrase level, which are totally different from state-of-the-art solutions. I proposed an original approach based on ...

This paper analyzes the issues raised by the change of ideology and the underlying meanings in five FitzGerald's translations of Khayyám's quatrains according to the theories of certain translation scholars such as André Lefevere and Antoine Berman. With regard to the fact that the British translator has given a harmonizing beauty and an epicurean flavor of his own to Khayyám's Rubáiyát, could it be claimed that translator's voice is louder than the author's? From the transcreation point of view, one could wonder whether FitzGerald did maintain the intent, style, tone, and content of the Persian quatrains. Do FitzGerald's translations evoke the same emotions and does it carry the same implications in English as Khayyám's Rubáiyát does in Persian. In general, from a postcolonial perspective, FitzGerald's five English translations could offer interesting and fertile ground for investigating the effects of power relationship between the colonizer and the colonized text during the Victorian age in England.

Keywords: Khayyám, quatrains, English translations, the colonizer, the colonized text.

The present paper delves into business and economic English and Arabic texts to describe the language and translator's norms and to justify these norms with regards of voices translation. The sample is collected manually from two e-portals where 20 texts were drawn from each website. It is found that translators use oblique translation methods to render passive constructions into Arabic in their endeavor to attain more idiomatic Arabic. Although translators are inclined to use the active voice more than the passive, this usage is mostly limited to dynamic verbs where English active stative verbs were modulated to passive Arabic beside the reduced adjectival phrases. The only gain of meaning or effect is achieved when the active English stative verbs became dynamic Arabic passives in order to give a stronger reporting of information. The findings contribute in characterizing the business and economic voice' behavior in English and Arabic in an attempt to integrate the findings with the findings of other genres.

37 p. ; This rapid response summarizes global research evidence drawn from many sources inthe research literature, mainly systematic reviews. It does not contain recommendations,which would have required the authors to make judgements based on personal valuesand preferences.This rapid response seeks to respond to the scientific information needs of politiciansand policy-makers to tackle this pandemic. A distinctive feature of this process is theuse of systematic and explicit methods to identify, select, appraise and synthesize dataand information from the included studies. This rapid response was conducted over 15business days and presents evidence for policy-makers in a concise and comprehensiblemanner.