1. Mobile and Pervasive Computing - 8 Natural Language Processing Presented by: Dr. Adeel Akram University of Engineering and Technology, Taxila,Pakistan http://web.uettaxila.edu.pk/CMS/SP2014/teMPCms

2. Outline  Natural Language Processing  Human Computer Dialog Systems  Problems and Success in HCD  Machine Translation  Example based Machine Translation  Projects

3. What is Natural Language Processing?  NLP is an interdisciplinary field that uses computational methods to:  Investigate the properties of written human language and model the cognitive mechanisms underlying the understanding and production of written language.  Develop novel practical applications involving the intelligent processing of written human language by computer.

4. What is NLP? (cont.)  NLP plays a big part in Machine learning techniques:  automating the construction and adaptation of machine dictionaries  modeling human agents' desires and beliefs  essential component of NLP  closer to AI  We will focus on two main types of NLP:  Human-Computer Dialogue Systems  Machine Translation

5. Human-Computer Dialogue Systems  Usually with the computer modelling a human dialogue participant  Will be able:  To converse in similar linguistic style  Discuss the topic  Hopefully teach

6. Current Capabilities of Dialogue Systems  Simple voice communication with machines  Personal computers  Interactive answering machines  Voice dialing of mobile telephones  Vehicle systems  Can access online as well as stored information  Currently working to improve

7. The Future of H-C Dialogue Systems  The final end result of human computer dialogue systems:  Seamless spoken interaction between a computer and a human  This would be a major component of making an AI that can pass the Turing Test  Be able to have a computer function as a teacher

8. Human Computer Dialogue in Fiction  Halo's Cortana AI  Made from models of a real human brain  Made to run the ship  Made very human conversations  Ender's Game series: Jane  Made from "philotic connection"  Human conversation

9. Problems of Human-Computer Dialogue  At the moment, most common computer dialogue systems (call systems, chatter bots, etc.) cannot handle arbitrary input  In many cases, the computer can only respond to "expected" speech  Call systems often compensate with "Sorry, I didn't get that," when something unexpected is said.

10. Problems of Human-Computer Dialogue  Computers need to be able to learn and process colloquial speech  Needed to understand informal speakers:  Understanding varied responses for call systems  Accounting for variations in spoken numbers  Processing colloquialisms is also necessary for seamless dialogue, where the computer must avoid sounding too formal  John Connor: "No, no, no, no. You gotta listen to the way people talk. You don't say 'affirmative,' or [stuff] like that. You say 'no problemo.' "

11. Successes of Human- Computer Dialogue  So far, human-computer dialogue has been most successful in applications where information about a specific topic is sought from the computer.  Electronic calling systems: company-specific  Travel agents: specific to an airline or destination  However, more complex systems of human-computer dialogue have been produced which can interpret more varied input.  Physics tutoring system (ITSPOKE) which can analyze and explain errors in the response to a physics problem.  Allows for more complex input than "Yes," "No," or "Flight UA- 93"  These still cannot compare to true human-human dialogue.

12. Machine Translation  Important for:  accessing information in a foreign language  communication with speakers of other languages  The majority of documents on the world wide web are in languages other than English

13. Statistical Translation  Rule based  Works relatively well with large sets of data  Used probability to translate text  Natural translations  Google

14. Example Based Translation  Converts "parallel" lines of text between language  Only accurate for simple lines  Minimal pairs are easy  Analogy based

15. Future of Machine Translation  Goal:  Aim to be able to flawlessly translate languages  Link Human-Computer Dialogue and Machine Translation  Have someone be able to talk in one language to a computer, translate for another person  Translated Video Chat

16. Machine Translation in Fiction  Star Wars: C-3P0  Interpreter  Could hear and translate alien languages  Final goal of machine translation  Star Trek: Universal Translator  Computer can seamlessly translate alien languages

17. Problems  Works well only with predictable texts.  Doesn't work well with domains where people want translation the most:  spontaneous conversations  in person  on the telephone  and on the Internet.

18. Problems  Computers can't deal with ambiguity, syntactic irregularity, multiple word meanings and the influence of context.  Time flies like an arrow.  Fruit flies like a banana.  Accurate translation requires an understanding of the text, situation, and a lot of facts about the world in general.  The box is in the pen.

19. Problems  The sign is describing a restaurant (the Chinese text, 餐 厅, means "dining hall").  In the process of making the sign, the producers tried to translate Chinese text into English with a machine translation system, but the software didn't work, producing the error message, "Translation Server Error."  The software's user didn't know English and thought the error message was the translation.

20. Successes  Product knowledge bases need to be translated into multiple languages  Hiring a large multilingual support staff is expensive  Machine translation is cheaper and accurate with predictable texts.  Microsoft, Apple, Google, Autodesk, Symantec, and Intel use it.  Makes customers happy  Still readable though slightly chunkier than human translations

21. Videos  The Smartphone Reinvented Around You - Windows Phone (United States) The Smartphone Reinvented Around You - Windows Phone (United States)  Cortana vs Siri vs Google Now battle Cortana vs Siri vs Google Now battle  Cortana Windows Phone 8.1 Demo - Microsoft Build 02_04_2014

22. Assignment # 4  Give Presentation on any one of the following projects  Apple Sri  Google Now  Microsoft Cortana

23. Questions???