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Human+Machine:MT Use in Lingosail
Yongpeng WEI 2016.04.25
TAUS Executive Forum Beijing 2016
About LingosailServices• Translation Technology• Corpus / Term-base Construction• Vertical MT Training• On-line CAT Customization
• Translation (MTPE) Service• MTPE production• MTPE training
Markets • Intellectual Properties • Cross-border E-Commerce• Internet Finance• …
What’s new for…Machine Translation:• Hybrid of statistical approaches and linguistic knowledge• Neural Machine Translation• Knowledge Graphs• …
Human Translation: • Crowd sourcing • Data sharing• Workflow automation• Writing for Translation• …
Why Human+Machine?
Easier Entry
• Lower requirement for domain knowledge
• Lower cost of learning and self-improvement for translators
Higher Efficiency
• Speed-up search and verification process
• Reduce repetitions• Reduce typing time• Reduce elementary
mistakes
More Scalable
Management
• Unify workflow• Increase
standardization
MTPE: Translator’s story(1)
Zhang 23 LibraStudent Major in English
Q: How long have you taken part in MTPE project?A: Two months. Q: What do you think MTPE is different from common translation?
A: Efficiency has been improved in significant measure(from 500 words/h to 750-1000 words/h). It has also shaped my translation style and thinking mode. However, if the MT result and the terms could not be easily confirmed by the translator, he/she need more other resources to verify the translation, then the process looks like common translation.Q:Recent monthly income?A:3500 Yuan (As an intern)
MTPE: Translator’s story(2)
Sun 24 AquariusFull-time Major in Japanese
Q: How long have you taken part in MTPE project?A: Five months. Q: What do you think MTPE is different from common translation?
A: I think it is easier to start. Some sentences are hard to understand and organize. MT gives helpful clues for me.Q:Recent monthly income?A:About 10000 Yuan (As an in-house translator).
MTPE: Translator’s story(3)
Han 25 AriesPart-time Major in Japanese
Q: How long have you taken part in MTPE project?A: Nearly one year (part-time). Q: What do you think MTPE is different from common translation? A: The translation system and the term base are powerful. For some of the MT results, you need only to adjust the word orders. It largely increases the efficiency, as well as the accuracy. Q:Recent monthly income?A:About 9000 Yuan (As a part-time translator).
1) MT is useful (in PE production), for ◦ Efficiency ◦ Quality◦ Scalability
2) Confidence is the key, so vertical MT training is a must◦ Domain specific◦ Find out the reliable parts (Training needed for translators)
3) Terminology plays an important role◦ Pre-translating: extract & check◦ On-translating: applied into MT◦ Post-translating: collection for future use
What are learned from these stories?
Terminologies applied into MTPE
TermsAnnotatio
nApplied into MT results
Second Scenario: Terminology Extraction
1. Monolingual Term Extract◦ MT used for: Term translation (in the context)◦ MT used for: Term recognition ( EBMT-based)
Second Scenario: Terminology Extraction
2. Bilingual Term Extract◦ MT used for: Word/Phrase Alignment◦ Term extracted for: reference term pairs (pre-trans)◦ Term extracted for: term pairs collection (post-trans)
Third Scenario: Cross-language IR
1. For Clients: CLIR for Database (e.g. patents)◦ MT used for: large volume of documents in the DB◦ Accuracy of Keywords(Terminologies)◦ Document similarity
2. For Translators: Find reference documents (in target language)◦ MT used for: document to be translated◦ Sentence similarity◦ Document similarity
Expectations for MT’s future use
Lower deploying threshold◦ Affordable computing capability (esp. for Neural MT)◦ Less corpus requirement◦ Acknowledged Quality Metrics
Involving deeper knowledge base◦ Terminology is the first step◦ Knowledge Graph
More interactive◦ Real-time interactions (e.g. Input Method)◦ Feedback from end-users◦ Dynamic user behaviors
