Automatic Improvement of Machine Translation Systems: recycling non-expert user feedback

Price: $93.00
(as of Dec 28,2024 15:56:01 UTC – Details)

Publisher ‏ : ‎ VDM Verlag Dr. Müller (September 10, 2009)
Language ‏ : ‎ English
Paperback ‏ : ‎ 196 pages
ISBN-10 ‏ : ‎ 3639200446
ISBN-13 ‏ : ‎ 978-3639200447
Item Weight ‏ : ‎ 10.4 ounces
Dimensions ‏ : ‎ 5.91 x 0.45 x 8.66 inches

Machine translation systems have made significant advancements in recent years, thanks to the continuous feedback received from users. However, one challenge that researchers face is the quality and relevance of the feedback provided by non-expert users. A new approach to address this issue is through the automatic improvement of machine translation systems by recycling non-expert user feedback.

By leveraging advanced machine learning algorithms, researchers can analyze and categorize non-expert user feedback to identify patterns and trends in translation errors. This data can then be used to fine-tune the machine translation models, leading to more accurate and reliable translations.

One key benefit of this approach is that it allows for a more scalable and efficient way to improve machine translation systems. Instead of relying solely on expert linguists to provide feedback, the system can automatically extract valuable insights from a larger pool of non-expert users.

Furthermore, by continuously recycling and updating the machine translation models based on user feedback, the system can adapt to changing language trends and nuances in real-time. This dynamic approach ensures that the translation quality remains high and relevant to users’ needs.

Overall, the automatic improvement of machine translation systems through recycling non-expert user feedback is a promising approach that can lead to more accurate and reliable translations for users around the world.
#Automatic #Improvement #Machine #Translation #Systems #recycling #nonexpert #user #feedback