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Say It For Me!. Team Members. Name: Huiqi Wang (Angel) Major: CSE and ECON Interest: Travel, outdoor sports. Name: Yiqing Wang Major: CSE and ART Interest: Cooking, Swimming. Team Members. Name: David Mah Major: CSE Anime, Tennis, Longboarding, Linux Name: Aswin Pranam
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Team Members Name: Huiqi Wang (Angel) Major: CSE and ECON Interest: Travel, outdoor sports Name: Yiqing Wang Major: CSE and ART Interest: Cooking, Swimming
Team Members Name: David Mah Major: CSE Anime, Tennis, Longboarding, Linux Name: Aswin Pranam Major: Informatics Interests: Basketball, Reading
Concept Mapping Forms of communication • Picture • Video • audio Situations one might need another language • Tourism • Language Study • Business Language Concepts • Reading • Speaking • Listening • Writing Translation Tools • http://lang-8.com/ (Social Community where people correct each others’ writing) • Crowd sourced AI (community/user translate?) • Translate engine (google translate) • Grammar correction Translation: Difficulties in automated translation • different languages • need translations quickly • multiple translations -> choose(how do you know what is correct) • translate checking -> correctness (the same as i just wrote above) People • ethnicity • Pronunciation (British/American) • Target users • communication How technology can fit in • download • recognition
Top 3 Problems 1. What Makes a 'Correct' Translation? Any translating tool needs to take culture and context into account, or translations won't actually be 'correct'. 2. Few Ways to Talk Across a Language Barrier Images, Audio, and Video can be used to convey translation information and concepts. (which could only possibly work using technology)
Top 3 Problems 3. Translations are needed quickly (often in real-time) While technology can be used to transfer translations/information very quickly, designing a system to deliver good translations is a balancing act between speed and correctness. It's not worth sending translations instantly if they are lousy.
Top Problem - Overview What Makes a 'Correct' Translation? Any translating tool needs to take culture and context into account, or translations won't actually be 'correct'. This is significant because a translation that doesn't accurately reflect the original idea is useless (possibly harmful). Stakeholders involve anybody who needs to communicate across a language barrier, whether for casual or formal situations. Precedents? Lousy automated translation tools. Social translation communities (not realtime translation). Handheld Electronic Dictionaries.
What Makes This The Top Problem What Makes a 'Correct' Translation? Reliability in translations is why there isn't a true prevalent real-time translation solution. There are a few solutions to smaller relevant problems, but the systems are either not advanced enough to be used in real-time or not reliable enough for anyone to want to use.
Significance What reliable translation can bring: • Verification of existing translations observed in the world. • A lack of frustration/awkwardness from bad translations • Trustworthy communication across a language barrier
Stakeholders - Tourists - Language learners - Business people - Developers/designers - Native speakers - Foreign speakers - Translators (crowdsourcing)
Competition I - How people currently handle real-time translation Electronic Dictionaries (eg. Casio) are sold to a wide range of users who need a "pocket dictionary" for popular languages. Using an electronic dictionary is slow and unreliable. Translations are on a word by word basis, which does not deliver true accuracy based on situational context. The choices of languages are limited, and options (languages, sound, writing pad) can be expensive.
Competition II - Automated Translation Tools Google Translateis amachine-translation service provided by Google Inc. to translate written text from one language into another. Google Translate is fast and supports many languages, but its word-to-word translation makes the result unreliable. Often people take [incorrect] translations for granted, which can be harmful.
Competition III - Social Translation Communities Lang-8 is an example of a online community of translators. People translate and correct each others' writing for the sake of learning/study. Lang-8 is irrelevant to real-time translations(this would be awesome), but their existence makes for a good proof of concept that people can offer to translate for each other.