<b>Computers and translation</b> : A translator’s guide. Ed. by Harold Somers. Amsterdam: John Benjamins, 2003. Pp. xvi, 351. ISBN 1588113779. $115 (Hb).
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Résumé
Reviewed by: Computers and translation: A translator’s guide ed. by Harold Somers Shaoxiang Wang Computers and translation: A translator’s guide. Ed. by Harold Somers. Amsterdam: John Benjamins, 2003. Pp. xvi, 351. ISBN 1588113779. $115 (Hb). How can computers help translators and their profession? This is the question Harold Somers and other authors address in Computers and translation: A translator’s guide, developing the view that computers can become an essential tool that will make the translators’ job better. The seventeen chapters in this book fall roughly into two sections, with the first (Chs. 1–7) focusing on the uses of computers in translators’ work and the second (Chs. 8–17) on machine translation (MT). The first three chapters are contributed by Harold Somers. While the opening chapter, ‘Introduction’, sketches the history of MT and provides an overview of the volume, Ch. 2 describes the translator’s workstation as the ‘most cost-effective facility’ for translators (28). Ch. 3 takes a special look at translation memory. In ‘Terminology tools for translators’, Lynne Bowker draws our attention to a variety of terminology tools. Bert Esselink, in ‘Localisation and translation’, introduces the basics of localization and traces its history back to the early 1980s. In ‘Translation technologies and minority languages’, Somers takes up the issue of computer-aided translation (CAT) and minority languages and projects its development. Sara Laviosa’s ‘Corpora and the translator’ outlines some of the current and potential uses of corpora in the empirical study of translation, translator training, and professional training. The remainder of the volume focuses more on MT. In ‘Why translation is difficult for computers’, Doug Arnold looks closely at the difficulties involved in MT in the light of the nature of translation. In ‘The relevance of linguistics for machine translation’, Paul Bennett considers some rigorous and systematic ways in which linguistics can be of use in MT systems. W. John Hutchins, in ‘Commercial systems: The state of the art’, reports on the current status and potentials of commercial MT systems and translation tools. In ‘Inside commercial machine translation’, Scott Bennett and Lauri Gerber explore commercial MT systems from the developer’s point of view. In ‘Going live on the internet’, Jin Yang and Elke Lange demystify the first free online translation service. In ‘How to evaluate machine translation’, John S. White [End Page 544] highlights the importance of evaluation in MT and, more importantly, alerts the researcher to its pitfalls. Eric Nyberg, Teruko Mitamura, and Willem-Olaf Huijsen, in ‘Controlled language for authoring and translation’, explain how controlled language can be applied to MT to ensure better quality output. In ‘Sublanguage’, Somers, also aiming at getting the best out of MT, discusses a successful sublanguage MT system—the Canadian Météo system—and analyzes its implication for future MT development. In ‘Post-editing’, Jeffrey Allen discusses the relevance, importance, and characteristics of post-editing. Finally, in ‘Machine translation in the classroom’, Somers considers the application of MT and CAT tools to the teaching of translation. Focusing on practical and usable MT and CAT tools, this volume should be of interest to anyone interested in language and translation. Shaoxiang Wang Fujian Teachers University Copyright © 2005 Linguistic Society of America
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Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.
Scores Codex et Gemma par catégorie
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,000 | 0,000 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,000 | 0,001 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,000 | 0,001 |
| Science ouverte | 0,001 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,000 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,000 | 0,000 |
Scores machine (provisoires)
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Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découle