Mobile and Pervasive Computing - 8

Natural Language Processing

Presented by: Dr. Adeel AkramUniversity of Engineering and Technology,

Taxila,Pakistan

http://web.uettaxila.edu.pk/CMS/SP2014/teMPCms

Outline

Natural Language Processing Human Computer Dialog Systems Problems and Success in HCD Machine Translation Example based Machine

Translation Projects

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.

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

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

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

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

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

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.

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.' "

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.

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

Statistical Translation

Rule based

Works relatively well with large sets of data

Used probability to translate text

Natural translations

Google

Example Based Translation

Converts "parallel" lines of text between language

Only accurate for simple lines

Minimal pairs are easy

Analogy based

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

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

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.

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. 

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.

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

Videos

The Smartphone Reinvented Around You - Windows Phone (United States)

Cortana vs Siri vs Google Now battle

Cortana Windows Phone 8.1 Demo - Microsoft Build 02_04_2014

Assignment # 4

Give Presentation on any one of the following projectsApple SriGoogle NowMicrosoft Cortana

Questions???