MSRA won in eight out of eleven machine translation tasks it undertook as part of the challenge
Microsoft Research Asia (MSRA) has achieved eight top places in the recent machine translation challenge organized by the 2019 fourth Conference on Machine Translation (WMT19), out of the eleven tasks it undertook. Overall, there are nineteen machine translation categories in WMT this year.
MSRA achieved first place in machine translation tasks for Chinese-English, English-Finnish, English-German, English-Lithuanian, French-German, German-English, German-French and Russian-English. Three other tasks were placed second in their respective categories, which included English-Kazakh, Finnish-English and Lithuanian-English.
As one of the leading machine translation competition globally, WMT is a platform for leading researchers to demonstrate their solutions, as well as to understand the continuous evolvement of machine translation technology. Now in its 14th year, more than 50 teams globally from technology companies, leading academic institutions and universities participated in a bid to demonstrate their machine translation capabilities.
The organizers aimed to evaluate current machine translation techniques for the languages other than English, as well as to examine the challenges between European languages, including low resource and morphologically rich languages.
Improvements to Multi-dimensional Algorithms for Better Machine Translation Outcomes
“This year, the MSRA team applied innovative algorithms to its system, which significantly improved the quality of the machine translation results. These algorithms were used to improve the platform’s learning mechanism, pre-training, network architecture optimization, data enhancement and other processes required so that the system can perform better,” explains Tie-Yan Liu, Assistant Managing Director of MSRA.
The innovative algorithms leveraged this year include:
- MADL : Multi-agent dual learning
- MASS : Masked sequence to sequence pre-training
- NAO : Automatic neural architecture optimization
- SCA : Soft contextual data augmentation
The achievement follows the 2018 breakthrough whereby researchers in MSRA and Microsoft Research U.S. labs reached human parity on a commonly used test set of news stories, called newstest2017, which was developed by a group of industry and academic partners and released at WMT17. The system is able to translate sentence of news articles from Chinese to English with the same quality and accuracy as a person.
“The realm of machine translation will continue to evolve with better algorithms, data set and technology. However, much of our research today is really inspired by how we humans do things. Language is complex and nuanced, as people can use different words to express the exact same concept. Hence, developing multi-dimensional algorithms is important in evolving machine translation systems so that they can deliver better outcomes,” said Liu. “Our achievement at WMT19 serves to the further development of the field, whereby we hope that machine translation can become better in the years to come.”
For example, Microsoft Translator, a multilingual machine translation cloud service, has integrated some of the previous solutions developed by Microsoft Research teams globally to enhance the accuracy of the tool. Now, the research teams plan to integrate the new algorithms used for this year’s WMT challenge to improve its offering.
Archive
- October 2024(44)
- September 2024(94)
- August 2024(100)
- July 2024(99)
- June 2024(126)
- May 2024(155)
- April 2024(123)
- March 2024(112)
- February 2024(109)
- January 2024(95)
- December 2023(56)
- November 2023(86)
- October 2023(97)
- September 2023(89)
- August 2023(101)
- July 2023(104)
- June 2023(113)
- May 2023(103)
- April 2023(93)
- March 2023(129)
- February 2023(77)
- January 2023(91)
- December 2022(90)
- November 2022(125)
- October 2022(117)
- September 2022(137)
- August 2022(119)
- July 2022(99)
- June 2022(128)
- May 2022(112)
- April 2022(108)
- March 2022(121)
- February 2022(93)
- January 2022(110)
- December 2021(92)
- November 2021(107)
- October 2021(101)
- September 2021(81)
- August 2021(74)
- July 2021(78)
- June 2021(92)
- May 2021(67)
- April 2021(79)
- March 2021(79)
- February 2021(58)
- January 2021(55)
- December 2020(56)
- November 2020(59)
- October 2020(78)
- September 2020(72)
- August 2020(64)
- July 2020(71)
- June 2020(74)
- May 2020(50)
- April 2020(71)
- March 2020(71)
- February 2020(58)
- January 2020(62)
- December 2019(57)
- November 2019(64)
- October 2019(25)
- September 2019(24)
- August 2019(14)
- July 2019(23)
- June 2019(54)
- May 2019(82)
- April 2019(76)
- March 2019(71)
- February 2019(67)
- January 2019(75)
- December 2018(44)
- November 2018(47)
- October 2018(74)
- September 2018(54)
- August 2018(61)
- July 2018(72)
- June 2018(62)
- May 2018(62)
- April 2018(73)
- March 2018(76)
- February 2018(8)
- January 2018(7)
- December 2017(6)
- November 2017(8)
- October 2017(3)
- September 2017(4)
- August 2017(4)
- July 2017(2)
- June 2017(5)
- May 2017(6)
- April 2017(11)
- March 2017(8)
- February 2017(16)
- January 2017(10)
- December 2016(12)
- November 2016(20)
- October 2016(7)
- September 2016(102)
- August 2016(168)
- July 2016(141)
- June 2016(149)
- May 2016(117)
- April 2016(59)
- March 2016(85)
- February 2016(153)
- December 2015(150)