Google Translate Gets Voltaire
Literary Translation and the Age of Artificial Intelligence
Bibliographic Data
| ID | 12879207 |
|---|---|
| Authors | Peter Constantine (University of Connecticut, corresponding author) |
| Year | 2019 |
| Volume | 23 |
| Issue | 4 |
| Pages | 471-479 |
| Publication date | 2019-08-08 |
| Peer Reviewed | Yes |
| Open Access | No |
| Type | ARTICLE |
| Venue | Contemporary French and Francophone Studies (JOURNAL) |
| Journal identifiers | ISSN: 1740-9292 • E-ISSN: 1740-9306 |
| Publisher | Routledge (PUBLISHER • GB) |
| DOI | 10.1080/17409292.2019.1694798 |
| OpenAlex | W3013290779 |
| Language | EN |
| Citations received | 7 |
| References cited | 1 |
In the fall of 2016, users of Google Translate working from French to English and English to French saw a marked improvement in the quality of the translated texts. Google Translate was beginning to develop from a purely phrase-based statistical machine translation system into a system that uses deep learning and artificial neural networks that can adapt and learn in reaction to all they encounter. The Google Translate development team has been working on expanding and strengthening the system’s capability of pragmatic analysis. This capability entails extracting useful information from a text so that its meaning can be accurately inferred in an attempt to overcome the vagueness and ambiguity inherent in language, which have remained the greatest hurdles to effective machine translation. This article explores the potential of Google Translate to provide increasingly competent translations of literary texts. Using passages from the works of Voltaire translated by Google Translate into English, this article explores both the successes and the ongoing problems faced by new generations of Google Translate, and of machine translation systems in general, as their developers seek to overcome the hurdles of identifying and rendering style, nuance, and ambiguity in language
Ambiguity · Machine translation · Natural language processing · Phrase · Rendering (computer graphics · Vagueness · Computer Science · Natural Language Processing Techniques · Artificial Intelligence
Taming AI for The Little Prince
Dialectal and/or Archaic Words in the Translation of Poetry
The Use of Artificial Intelligence in the Rendition of Certain Articles of Ḥanbalī Sharīʿa Code into English
Human and machine translation of occasionalisms in literary texts
Potential of Machine Translation in Museum Media Discourse
Acculturation and identity crisis through renaming
Can machine translation of literary texts fool stylometry
| Unique citing works | 7 |
|---|---|
| Citations per year | 2,33 |
| Citation span | 2023 - 2026 (4) |
| Citation velocity | current |
| Highly cited | No |
| Citation types | Neutral: 7 |