49 1 computer language by don l. f. nilsen and alleen pace nilsen

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COMPUTER COMPUTER LANGUAGELANGUAGE

by Don L. F. Nilsenby Don L. F. Nilsen

and Alleen Pace Nilsenand Alleen Pace Nilsen

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Verbal LiteracyVerbal Literacyvs. Number Literacyvs. Number Literacy

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BOTTOM-UP AND TOP-DOWN PROCESSINGBOTTOM-UP AND TOP-DOWN PROCESSING

Bottom-up processing relates to Bottom-up processing relates to decoding. You start with the actual decoding. You start with the actual sounds, letters, morphemes, etc. and sounds, letters, morphemes, etc. and figure out the words, phrases, figure out the words, phrases, clauses, sentences, paragraphs, etc.clauses, sentences, paragraphs, etc.

Top-down processing is based on Top-down processing is based on reasoning. You make a reasoning. You make a generalization and see how well the generalization and see how well the sounds, letters, morphemes, etc. sounds, letters, morphemes, etc. support your generalization.support your generalization.

(Fromkin Rodman Hyams 369)(Fromkin Rodman Hyams 369)

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Top-down reasoning is powerful, Top-down reasoning is powerful, but it can be dangerous if it is but it can be dangerous if it is not accompanied by bottom-up not accompanied by bottom-up reasoning.reasoning.

For example, Otto Jesperson For example, Otto Jesperson assumed that men were better assumed that men were better thinkers than women.thinkers than women.

He conducted an experiment in He conducted an experiment in which men and women read a which men and women read a story and were given a quiz.story and were given a quiz.

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The women responded more quickly The women responded more quickly and more accurately than the men, and more accurately than the men, which was not what Jacobson had which was not what Jacobson had expected.expected.

So he concluded that women’s minds So he concluded that women’s minds have “vacant chambers” that men’s have “vacant chambers” that men’s minds don’t have.minds don’t have.

This allowed Jacobson to account for This allowed Jacobson to account for his evidence while at the same time his evidence while at the same time not disproving his original hypothesis not disproving his original hypothesis that men were better thinkers than that men were better thinkers than women.women.

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COMPUTER WORDS AND METAPHORSCOMPUTER WORDS AND METAPHORS

COMPUTER WORDS: bits, bytes, code police, COMPUTER WORDS: bits, bytes, code police, cyberspace, future shock, hackers, hard cyberspace, future shock, hackers, hard copy, menu, third wave, user-friendly copy, menu, third wave, user-friendly

COMPUTER METAPHORS: 42, bug, cookies, COMPUTER METAPHORS: 42, bug, cookies, GIGO, great runes, heavy wizardry, Lotus GIGO, great runes, heavy wizardry, Lotus Software, Melvyl (California Library Software, Melvyl (California Library System), a sagan, snail mail, Sorcerer’s System), a sagan, snail mail, Sorcerer’s Apprentice mode, Trojan Horse, USLT, Apprentice mode, Trojan Horse, USLT, vulcan nerve pinch, web, YABA compatiblevulcan nerve pinch, web, YABA compatible

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CONCORDANCECONCORDANCE

A Concordance checks for word A Concordance checks for word frequency and word associations. frequency and word associations.

Word associations are determined Word associations are determined by providing a window of three by providing a window of three words (more or less) on each side words (more or less) on each side of the targeted word.of the targeted word.

(Fromkin Rodman Hyams 379) (Fromkin Rodman Hyams 379)

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ELIZAELIZA

ELIZA is a program designed to pass ELIZA is a program designed to pass the turing test. If a person the turing test. If a person communicating with ELIZA cannot tell communicating with ELIZA cannot tell whether or not ELIZA is a human, whether or not ELIZA is a human, then ELIZA passes the turing test.then ELIZA passes the turing test.

ELIZA claims to be a psychiatrist ELIZA claims to be a psychiatrist talking to a patient. ELIZA, like a talking to a patient. ELIZA, like a psychiatrist, is attempting to get psychiatrist, is attempting to get rather than give information:rather than give information:

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PATIENT: Men are all alike.PATIENT: Men are all alike. ELIZA: In what way?ELIZA: In what way? PATIENT: They’re always bugging me PATIENT: They’re always bugging me

about something or other.about something or other. ELIZA: Can you think of a specific ELIZA: Can you think of a specific

example?example? PATIENT: Well, my boyfriend made PATIENT: Well, my boyfriend made

me come here.me come here. ELIZA: Your boyfriend made you come ELIZA: Your boyfriend made you come

here?here? PATIENT: He says I’m depressed much PATIENT: He says I’m depressed much

of the time.of the time. ELIZA: I am sorry to hear that you are ELIZA: I am sorry to hear that you are

depressed.depressed. (Fromkin Rodman Hyams 389)(Fromkin Rodman Hyams 389)

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Victor Raskin fooled ELIZA by Victor Raskin fooled ELIZA by saying, “I don’t like my mother saying, “I don’t like my mother and I don’t want to talk about and I don’t want to talk about her.”her.”

ELIZA responded, “Tell me more ELIZA responded, “Tell me more about your mother.about your mother.

(Nilsen Nilsen & Combs 199)(Nilsen Nilsen & Combs 199)

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CIRCUIT FIX-IT SHOPCIRCUIT FIX-IT SHOP Twenty-five years after ELIZA, a program Twenty-five years after ELIZA, a program

named “Circuit Fix-It Shop” was developed:named “Circuit Fix-It Shop” was developed:

COMPUTER: This is the circuit fix-it shop. COMPUTER: This is the circuit fix-it shop. How may I help you?How may I help you?

TECHNICIAN: I need to fix the RS111 circuit.TECHNICIAN: I need to fix the RS111 circuit. COMPUTER: I am familiar with that circuit. COMPUTER: I am familiar with that circuit.

The LED is supposed to be displaying The LED is supposed to be displaying alternatively blinking one and seven.alternatively blinking one and seven.

TECHNICIAN: Where is the LED?TECHNICIAN: Where is the LED?

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COMPUTER: In the middle right of the COMPUTER: In the middle right of the blue region is the LED.blue region is the LED.

TECHNICIAN: TECHNICIAN: No light.No light.

COMPUTER: What is the switch at COMPUTER: What is the switch at when the LED is off?when the LED is off?

TECHNICIAN: The switch is down.TECHNICIAN: The switch is down.

COMPUTER: You put up the switch.COMPUTER: You put up the switch. (Fromkin Rodman Hyams 390)(Fromkin Rodman Hyams 390)

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MORE SOPHISTICATED PROGRAMSMORE SOPHISTICATED PROGRAMS

Today more sophisticated programs Today more sophisticated programs are needed. One such program is the are needed. One such program is the little Paperclip guy that answers little Paperclip guy that answers questions in Microsoft Word.questions in Microsoft Word.

Another sophisticated program is Another sophisticated program is “Script Model Grammar” designed by “Script Model Grammar” designed by Roger Schank and Robert Abelson and Roger Schank and Robert Abelson and modified by linguist Victor Raskin and modified by linguist Victor Raskin and others at Purdue University and others at Purdue University and elsewhere.elsewhere.

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SAM: SCRIPT APPLIER MECHANISMSAM: SCRIPT APPLIER MECHANISM

Of course sentences need to be Of course sentences need to be parsed in Artificial Intelligence. But parsed in Artificial Intelligence. But constituents larger than a sentence constituents larger than a sentence must be parsed as well.must be parsed as well.

One of the devices for doing this One of the devices for doing this discourse parsing is the “Script discourse parsing is the “Script Applier Mechanism” devised by Roger Applier Mechanism” devised by Roger Schank and Robert Abelson and Schank and Robert Abelson and modified for humor and language play modified for humor and language play by Victor Raskin and others.by Victor Raskin and others.

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Note that a play or a movie has a Note that a play or a movie has a script for the actors to follow.script for the actors to follow.

The script in Artificial The script in Artificial Intelligence is the same, but it is Intelligence is the same, but it is much simpler. It is a “mundane much simpler. It is a “mundane script.”script.”

The “Restaurant Script,” for The “Restaurant Script,” for example involves a customer, a example involves a customer, a server, a cashier, etc.server, a cashier, etc.

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Props in the “Restaurant Script” include the Props in the “Restaurant Script” include the restaurant, the table, the menu, the food, the check, restaurant, the table, the menu, the food, the check, the payment, the tip, etc.the payment, the tip, etc.

The sequence of actions is as follows:The sequence of actions is as follows: 1. Customer goes to restaurant.1. Customer goes to restaurant. 2. Customer goes to table.2. Customer goes to table. 3. Server brings menu.3. Server brings menu. 4. Customer orders food.4. Customer orders food. 5. Server brings food.5. Server brings food. 6. Customer eats food.6. Customer eats food. 7. Server brings check.7. Server brings check. 8. Customer leaves tip for server.8. Customer leaves tip for server. 9. Customer gives payment to cashier.9. Customer gives payment to cashier. 10. Customer leaves restaurant.10. Customer leaves restaurant.

(Hendrix and Sacerdote 654)(Hendrix and Sacerdote 654) (Nilsen Nilsen & Combs 199)(Nilsen Nilsen & Combs 199)

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There are two exciting things about There are two exciting things about the Script Applier Mechanism. First, it the Script Applier Mechanism. First, it will be able to spot anything that is will be able to spot anything that is missing, added, or out of place in the missing, added, or out of place in the sequence of events and ask, “What’s sequence of events and ask, “What’s up.”up.”

Second, it is able to handle two Second, it is able to handle two scripts at the same time, so that it is scripts at the same time, so that it is capable of dealing with jokes, capable of dealing with jokes, language play, satire, irony, sarcasm, language play, satire, irony, sarcasm, parody, paradox and double entendre parody, paradox and double entendre in general.in general.

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PARSING PROBLEMSPARSING PROBLEMS GARDEN PATH: GARDEN PATH: The horse raced past the barn fell. The horse raced past the barn fell. After the child visited the doctor prescribed a course After the child visited the doctor prescribed a course

of injections.of injections. The doctor said the patient will die yesterday.The doctor said the patient will die yesterday.

(Fromkin Rodman Hyams 365, 373)(Fromkin Rodman Hyams 365, 373)

EMBEDDING: “Never imagine yourself not to be EMBEDDING: “Never imagine yourself not to be otherwise than what it might appear to others…to be otherwise than what it might appear to others…to be otherwise.”otherwise.” (Lewis Carroll’s (Lewis Carroll’s Alice’s Adventures in WonderlandAlice’s Adventures in Wonderland))


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RIGHT-BRANCHING VS. EMBEDDINGRIGHT-BRANCHING VS. EMBEDDING

RIGHT BRANCHING: This is the dog that RIGHT BRANCHING: This is the dog that worried the cat that killed the rat that ate worried the cat that killed the rat that ate the malt that lay in the house that Jack the malt that lay in the house that Jack built.built.

EMBEDDING: Jack built the house that the EMBEDDING: Jack built the house that the malt that the rat that the cat that the dog malt that the rat that the cat that the dog worried killed ate lay in.worried killed ate lay in.

NOTE Multiple embedding is OK for a NOTE Multiple embedding is OK for a computer, but not OK for the human brain.computer, but not OK for the human brain.

(Fromkin Rodman Hyams 373-374)(Fromkin Rodman Hyams 373-374)

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ANOMALOUS WORDS: A sniggle blick ANOMALOUS WORDS: A sniggle blick is procking a slar.is procking a slar.


METANALYSIS (incorrect phrase METANALYSIS (incorrect phrase breaking): breaking):

grade A vs. grey daygrade A vs. grey day night rate vs. nitratenight rate vs. nitrate


NOTE: English “adder” and “apron” NOTE: English “adder” and “apron” were borrowed incorrectly from the were borrowed incorrectly from the French expressions “un nadder” and French expressions “un nadder” and “un naperon” respectively“un naperon” respectively

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AMBIGUOUS SYNTAX IN NEWSPAPER AMBIGUOUS SYNTAX IN NEWSPAPER HEADLINES:HEADLINES:

Teacher Strikes Idle KidsTeacher Strikes Idle Kids

Enraged Cow Injures Farmer with AxEnraged Cow Injures Farmer with Ax

Killer Sentenced to Die for Second Killer Sentenced to Die for Second Time in 10 YearsTime in 10 Years

Stolen Painting Found by TreeStolen Painting Found by Tree (Fromkin Rodman Hyams 372)(Fromkin Rodman Hyams 372)

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REAL-WORLD KNOWLEDGEREAL-WORLD KNOWLEDGE Explain why the following sentences are Explain why the following sentences are

ambiguous to a computer but not to a ambiguous to a computer but not to a human:human:

A cheesecake was on the table. It was A cheesecake was on the table. It was delicious and was soon eaten.delicious and was soon eaten.

SIGN IN A CHURCH: For those of you who SIGN IN A CHURCH: For those of you who have children and don’t know it, we have a have children and don’t know it, we have a nursery downstairs.nursery downstairs.

NEWSPAPER AD: Our bikinis are exciting; NEWSPAPER AD: Our bikinis are exciting; they are simply the tops.they are simply the tops.


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ANTISMOKING CAMPAIGN SLOGAN: ANTISMOKING CAMPAIGN SLOGAN: It’s time we make smoking history.It’s time we make smoking history.

Do you know the time?Do you know the time? Concerned with spreading violence, Concerned with spreading violence,

the president called a press the president called a press conference.conference.

The ladies of the church have cast off The ladies of the church have cast off clothing of every kind and they may clothing of every kind and they may be seen in the church basement be seen in the church basement Friday.Friday.


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AMBIGUOUS NEWSPAPER HEADLINESAMBIGUOUS NEWSPAPER HEADLINES

Red Tape Holds Up New BridgeRed Tape Holds Up New Bridge

Kids Make Nutritious SnacksKids Make Nutritious Snacks

Sex Education Delayed, Teachers Sex Education Delayed, Teachers Request TrainingRequest Training


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SEMANTIC PRIMINGSEMANTIC PRIMING In the human brain, the word “doctor” is In the human brain, the word “doctor” is

more easily and more completely processed more easily and more completely processed if it is preceded by “nurse” than if it is if it is preceded by “nurse” than if it is preceded by “flower.”preceded by “flower.”

This is because “doctor” and “nurse” “are This is because “doctor” and “nurse” “are located in the same part of the mental located in the same part of the mental lexicon.”lexicon.”


This same feature could easily be built into This same feature could easily be built into Artificial Intelligence.Artificial Intelligence.

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SPEECH RECOGNITION SPEECH RECOGNITION & SPEECH SYNTHESIS& SPEECH SYNTHESIS

““Computational phonetics and phonology has two Computational phonetics and phonology has two concerns. The first is with programmng computers concerns. The first is with programmng computers to analyze the speech signal into its component to analyze the speech signal into its component phones and phonemes. phones and phonemes.

The second is to send the proper signals to an The second is to send the proper signals to an electronic speaker so that it enunciates the phones electronic speaker so that it enunciates the phones of the language and combines them into morphemes of the language and combines them into morphemes and words. and words.

The first of these is The first of these is speech recognitionspeech recognition; the second ; the second is is speech synthesisspeech synthesis.”.”


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““Machines which…imitate human Machines which…imitate human speech, are the most difficult to speech, are the most difficult to construct, so many are the construct, so many are the agencies engaged in uttering agencies engaged in uttering even a single word—so many are even a single word—so many are the inflections and variations of the inflections and variations of tone and articulation, that the tone and articulation, that the mechanician finds his ingenuity mechanician finds his ingenuity taxed to the utmost to imitate taxed to the utmost to imitate them.” them.”


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TO SYNTHESIZE SPEECH:TO SYNTHESIZE SPEECH:

1. Start with a tone at the same frequency as vibrating 1. Start with a tone at the same frequency as vibrating vocal cords (higher if a woman’s or child’s voice is being vocal cords (higher if a woman’s or child’s voice is being synthesized, lower for a man’s)synthesized, lower for a man’s)

2. Emphasize the harmonics corresponding to the formants 2. Emphasize the harmonics corresponding to the formants required for a particular vowel, liquid, or nasal quality.required for a particular vowel, liquid, or nasal quality.

3. Add hissing or buzzing for fricatives.3. Add hissing or buzzing for fricatives.

4. Add nasal resonances for nasal sounds.4. Add nasal resonances for nasal sounds.

5. Temporarily cut off sound to produce stops and 5. Temporarily cut off sound to produce stops and affricates….affricates….


A Sound Spectrogram will give an indication of some of the A Sound Spectrogram will give an indication of some of the variables of analyzing or synthesizing speech:variables of analyzing or synthesizing speech:

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SOUND SPECTROGRAMSOUND SPECTROGRAM(Fromkin Rodman Hyams 366)(Fromkin Rodman Hyams 366)

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SPELL CHECKERSPELL CHECKER

I have a spelling checker.I have a spelling checker. It came with my PC.It came with my PC. It plane lee marks four my revueIt plane lee marks four my revue Miss steaks aye can knot sea.Miss steaks aye can knot sea.


Explain why the spell checker is Explain why the spell checker is not working in the poem above.not working in the poem above.

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THEORIES AND MODELSTHEORIES AND MODELS In In The Physicist’s Conception of NatureThe Physicist’s Conception of Nature, ,

Manfred Eigen said, “A theory has only the Manfred Eigen said, “A theory has only the alternative of being right or wrong. A alternative of being right or wrong. A model has a third possibility: it may be model has a third possibility: it may be right, but irrelevant.”right, but irrelevant.”


Explain why a theory for Artificial Explain why a theory for Artificial Intelligence must be rigorous and at the Intelligence must be rigorous and at the same time allow for language play. In AI, same time allow for language play. In AI, are rigor and language play compatible are rigor and language play compatible concepts or not?concepts or not?

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TRANSLATIONTRANSLATION

““Translation is more than word-for-Translation is more than word-for-word replacement. Often there is no word replacement. Often there is no equivalent word in the target equivalent word in the target language, and the order of words may language, and the order of words may differ, as in translating from an SVO differ, as in translating from an SVO language like English to an SOV language like English to an SOV language like Japanese. There is also language like Japanese. There is also difficulty in translating idioms, difficulty in translating idioms, metaphors, jargon, and so on.”metaphors, jargon, and so on.”


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““Machine translation is often impeded Machine translation is often impeded by lexical and syntactic ambiguities, by lexical and syntactic ambiguities, structural disparities between the two structural disparities between the two languages, morphological languages, morphological complexities, and other cross-complexities, and other cross-linguistic differences.”linguistic differences.”


In the following examples consider In the following examples consider what information must be taken into what information must be taken into consideration for better machine consideration for better machine translation:translation:

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BUCHAREST HOTEL: The lift is being fixed for the next BUCHAREST HOTEL: The lift is being fixed for the next day. During that time we regret that you will be day. During that time we regret that you will be unbearable.unbearable.

SWISS NUNNERY HOSPITAL: The nuns harbor all SWISS NUNNERY HOSPITAL: The nuns harbor all diseases and have no respect for religion.diseases and have no respect for religion.

GERMAN HOTEL: All the water has been passed by the GERMAN HOTEL: All the water has been passed by the manager.manager.

ZURICH HOTEL: Because of the impropriety of ZURICH HOTEL: Because of the impropriety of entertaining guest of the opposite sex in the bedroom, entertaining guest of the opposite sex in the bedroom, it is suggested that the lobby be used for this purpose.it is suggested that the lobby be used for this purpose.

TURKEY: The government bans the smoking of TURKEY: The government bans the smoking of children.children.


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Having Fun Having Fun with Computer with Computer TerminologyTerminology

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10241024 When Alan Schoenfeld of the When Alan Schoenfeld of the

University of California at Berkeley University of California at Berkeley attended a conference on Artificial attended a conference on Artificial Intelligence, he was given Hotel Room Intelligence, he was given Hotel Room Number 1024.Number 1024.

Wow! he said.Wow! he said.

1024 is 2 to the tenth power. It is a 1024 is 2 to the tenth power. It is a kilobyte.kilobyte.

(Nilsen & Nilsen 98)(Nilsen & Nilsen 98)

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ACRONYMSACRONYMS Acronyms are so common in computer Acronyms are so common in computer

terminology that programmers make terminology that programmers make fun of them.fun of them.

““TLA” stands for “Three Letter TLA” stands for “Three Letter Acronym.”Acronym.”

““YABA” stands for “Yet Another YABA” stands for “Yet Another Bloody Acronym.”Bloody Acronym.”

““YABA Compatible” means that the YABA Compatible” means that the initials can be pronounced easily are initials can be pronounced easily are are not obscene.are not obscene.


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CHAT GROUPSCHAT GROUPS Linguist Susan Herring at the University of Texas, Linguist Susan Herring at the University of Texas,

Arlington studied the humor in chat groups. Her Arlington studied the humor in chat groups. Her results were as follows:results were as follows:

imaginary situations: 20 percentimaginary situations: 20 percent a mock persona: 14 percenta mock persona: 14 percent teasing: 13 percentteasing: 13 percent irony: 6 percentirony: 6 percent name play: 5 percentname play: 5 percent silliness: 4 percentsilliness: 4 percent real situations: 3 percentreal situations: 3 percent riddles: 2 percentriddles: 2 percent pretended misunderstandings: 2 percentpretended misunderstandings: 2 percent puns: 1 percentpuns: 1 percent


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EMOTICONSEMOTICONS In conversation we can show our emotions, but on In conversation we can show our emotions, but on

the internet this is difficult, so we use emoticons:the internet this is difficult, so we use emoticons: :-) Smilling:-) Smilling :-)))))))))) Really Smiling :-)))))))))) Really Smiling ;-) Winking;-) Winking :-* Kissing:-* Kissing I-0 YawningI-0 Yawning :-& Tongue-Tied:-& Tongue-Tied :’-{ Crying:’-{ Crying :-/ Undecided:-/ Undecided :-II Angry:-II Angry


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SCIENCE FICTION AND FANTASYSCIENCE FICTION AND FANTASY

Many computer terms come from Science Fiction and Many computer terms come from Science Fiction and Fantasy:Fantasy:

A huge network packet is a “Godzillagram” from A huge network packet is a “Godzillagram” from GodzillaGodzilla

Teenage hackers are “Munchkins” from Teenage hackers are “Munchkins” from The Wizard The Wizard of Ozof Oz

A mischievlous program is called a “wabbit” from A mischievlous program is called a “wabbit” from Elmer Fudd’s “You wascawwy wabbit.”Elmer Fudd’s “You wascawwy wabbit.”

A program that repeats itself indefinitely is said to A program that repeats itself indefinitely is said to be in “Sorcerer’s Apprentice Mode” from be in “Sorcerer’s Apprentice Mode” from FantasiaFantasia

The meaning of life, truth, and everything is “42” The meaning of life, truth, and everything is “42” from a computer in Douglas Adams’ novel.from a computer in Douglas Adams’ novel.


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When someone goes onto the internet When someone goes onto the internet to get information that is easily to get information that is easily available from the library the Cyber available from the library the Cyber Police might say, “USLT.” This means Police might say, “USLT.” This means “Use the Source, Luke!” from “Use the Source, Luke!” from StarwarsStarwars..

Another word from Another word from StarwarsStarwars is an is an “Obi-Wan Error.” This comes from the “Obi-Wan Error.” This comes from the name “Obi-Wan Kenobi” and refers to name “Obi-Wan Kenobi” and refers to an “off-by-one code,” as in an “off-by-one code,” as in 2001: A 2001: A Space OdysseySpace Odyssey where the computer is where the computer is named “HAL.” This comes from “IBM” named “HAL.” This comes from “IBM” but is the three letters before I, B, and but is the three letters before I, B, and M.M.


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In computer terminology a soft boot refers In computer terminology a soft boot refers to the hitting of “Control,” “Alternate” and to the hitting of “Control,” “Alternate” and “Delete” at the same time.“Delete” at the same time.

This is refered to as the “Vulcan Nerve This is refered to as the “Vulcan Nerve Pinch” from Pinch” from Star TrekStar Trek..

““Droid” from “Android” has become a suffix Droid” from “Android” has become a suffix in such words as “trendroids,” who follow in such words as “trendroids,” who follow trends, and “sales droids” which promise trends, and “sales droids” which promise customers things that can be delivered or customers things that can be delivered or are useless.are useless.

The “code police” and “net police” are The “code police” and “net police” are named after the “thought police” in George named after the “thought police” in George Orwell’s Orwell’s 19841984..

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SIGNATURESSIGNATURES

People like to create enigmatic and People like to create enigmatic and puzzing signatures. One user named puzzing signatures. One user named Eddie follows his signature with “Ceci Eddie follows his signature with “Ceci n’est pas une signature.”n’est pas une signature.”

This is an allusion to a painting of a This is an allusion to a painting of a pipe by René Magritte with the pipe by René Magritte with the disclaimer, “Ceci n’est pas une pipe.”disclaimer, “Ceci n’est pas une pipe.”


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TEXT MESSAGINGTEXT MESSAGING Since numbers and letters require Since numbers and letters require

more than a single stroke on cell more than a single stroke on cell phones, acronyms are often used:phones, acronyms are often used:

AFAIK: As far as I knowAFAIK: As far as I know BTW: By the wayBTW: By the way CUL or CUL8R: See you laterCUL or CUL8R: See you later GIGO: Garbage In Garbage OutGIGO: Garbage In Garbage Out GFR: Grime File ReaperGFR: Grime File Reaper LOL: Lots of LaughsLOL: Lots of Laughs OIC: Oh, I seeOIC: Oh, I see

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POS: Parent Over ShoulderPOS: Parent Over Shoulder ROTF: Rolling on the FloorROTF: Rolling on the Floor ROTFLMAO: Rolling on the Floor ROTFLMAO: Rolling on the Floor

Laughing My Ass OffLaughing My Ass Off RUOK: Are you OK?RUOK: Are you OK? TIA: Thanks in AdvanceTIA: Thanks in Advance WYSIWYG: What you See Is What You WYSIWYG: What you See Is What You

GetGet andand BCNU: Be Seein’ youBCNU: Be Seein’ you


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TWENTE, NETHERLANDSTWENTE, NETHERLANDS

• Every year there is an annual Every year there is an annual workshop on Language Technology workshop on Language Technology at the University of Twente.at the University of Twente.

• In 1996 this workshop was devoted In 1996 this workshop was devoted to “Automatic Interpretation and to “Automatic Interpretation and Generation of Verbal Humor.”Generation of Verbal Humor.”

• The papers at this conference had The papers at this conference had such titles as:such titles as:

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““Why do People Use Irony?”Why do People Use Irony?” ““Password Swordfish: Verbal Humour in the Password Swordfish: Verbal Humour in the

Interface.”Interface.” ““Computer Implementation of the General Theory of Computer Implementation of the General Theory of

Verbal Humor.”Verbal Humor.” ““Humor Theory beyond Jokes.”Humor Theory beyond Jokes.” ““Speculations on Story Puns.”Speculations on Story Puns.” ““Relevance Theory and Humorous Interpretations.”Relevance Theory and Humorous Interpretations.” ““What Sort of a Speech Act is the Joke?”What Sort of a Speech Act is the Joke?” ““A Neural Resolution of the Incongruity-Resoulution A Neural Resolution of the Incongruity-Resoulution

Theory of Humor”Theory of Humor” ““Humorous Analogy: Modeling the Humorous Analogy: Modeling the Devil’s Devil’s

DictionaryDictionary.”.” ““Why Is a Riddle Not Like a Metaphor?” andWhy Is a Riddle Not Like a Metaphor?” and ““An Attempt at Natural Humor from a Natural An Attempt at Natural Humor from a Natural

Language Robot.”Language Robot.” (Nilsen and Nilsen 98)(Nilsen and Nilsen 98)

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VIRUS JOKESVIRUS JOKES

AT&T Virus: Every three minutes AT&T Virus: Every three minutes it tells you what great service it tells you what great service you are getting.you are getting.

MCI Virus: Every three minutes it MCI Virus: Every three minutes it reminds you that you’re paying reminds you that you’re paying too much for the AT&T virus.too much for the AT&T virus.

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Paul Revere Virus: This Paul Revere Virus: This revolutionary virus does not revolutionary virus does not horse around. It warns you of horse around. It warns you of impending hard disk attack—impending hard disk attack—once if by LAN, twice if by C:>.once if by LAN, twice if by C:>.

New World Order Virus: Probably New World Order Virus: Probably harmless, but it makes a lot of harmless, but it makes a lot of people really mad just thinking people really mad just thinking about it.about it.


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!KURT VONNEGUT ON THE INTERNET!KURT VONNEGUT ON THE INTERNET

In August of 1997 a piece appeared In August of 1997 a piece appeared on the Internet by Kurt Vonnegut.on the Internet by Kurt Vonnegut.

When Vonnegut’s wife was given a When Vonnegut’s wife was given a copy of the article she was so pleased copy of the article she was so pleased with her clever husband that she with her clever husband that she forwarded a copy to their children.forwarded a copy to their children.

Vonnegut said that it was “funny and Vonnegut said that it was “funny and wise and charming,” but he said he wise and charming,” but he said he never wrote it.never wrote it.

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!!!! The article had actually been published by Mary The article had actually been published by Mary

Schmich in the Schmich in the Chicago TribuneChicago Tribune and then picked up and then picked up and redistributed by a computer hacker.and redistributed by a computer hacker.

Ian Fisher of Ian Fisher of The New York TimesThe New York Times said that as long said that as long as readers thought the piece was Vonnegut’s, they as readers thought the piece was Vonnegut’s, they viewed the Internet as a wonderful tool that could viewed the Internet as a wonderful tool that could keep people in touch with each other.keep people in touch with each other.

But when they learned it was a hoax, their But when they learned it was a hoax, their perception of the internet changed. The internet perception of the internet changed. The internet was now an unreliable hotbed of hoaxes and wild-was now an unreliable hotbed of hoaxes and wild-eyed conspiracies. eyed conspiracies.

Probably both opinions are true.Probably both opinions are true. (Nilsen & Nilsen 168)(Nilsen & Nilsen 168)

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!!!YOUTUBE!!!YOUTUBE

http://youtube.com/watch?v=2Fe110http://youtube.com/watch?v=2Fe110|Miz8|Miz8

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Web Site:

Encyclopedia of 20th Century American Humor. http://www.greenwood.com/catalog/OXHUMOR.aspx

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References # 1.References # 1.

Clark, Virginia, Paul Eschholz, and Alfred Rosa. Clark, Virginia, Paul Eschholz, and Alfred Rosa. Language: Readings Language: Readings in Language and Culture, 6th Editionin Language and Culture, 6th Edition. New York, NY: St. Martin’s . New York, NY: St. Martin’s Press, 1998.Press, 1998.

English, Katharine, ed. English, Katharine, ed. Most Popular Web Sites: The Best of the Net Most Popular Web Sites: The Best of the Net from A2Zfrom A2Z. Indianapolis, IN: Lycos Press, 1996.. Indianapolis, IN: Lycos Press, 1996.

Fromkin, Victoria, Robert Rodman, and Nina Hyams. “Language Fromkin, Victoria, Robert Rodman, and Nina Hyams. “Language Processing: Humans and Computers.” Processing: Humans and Computers.” An Introduction to An Introduction to Language, 8th EditionLanguage, 8th Edition. Boston, MA: Thomson Wadsworth, 2007, . Boston, MA: Thomson Wadsworth, 2007, 363-408.363-408.

Gralla, Preston. Gralla, Preston. How the Internet WorksHow the Internet Works. Emoryville, CA: Ziff-Daivs . Emoryville, CA: Ziff-Daivs Press, 1997.Press, 1997.

Hendrix, Gary G., and Earl D. Sacerdoti. “Natural-Languag Hendrix, Gary G., and Earl D. Sacerdoti. “Natural-Languag Processing: The Field in Perspective.” in Processing: The Field in Perspective.” in Language: Introductory Language: Introductory ReadingsReadings, 4, 4thth edition. Eds. Virginia P. Clark, Paul A. Eslchholz and edition. Eds. Virginia P. Clark, Paul A. Eslchholz and Alfred F. Rosa. New York, NY: St. Martin’s, 1985.Alfred F. Rosa. New York, NY: St. Martin’s, 1985.

Hulstijn, J., and A. Nijholt eds. Hulstijn, J., and A. Nijholt eds. Twente Workshop on Language Twente Workshop on Language Technology 12: Automatic Interpretation and Generation of Verbal Technology 12: Automatic Interpretation and Generation of Verbal HumorHumor. Twente, Netherlands: Univ of Twente Dept of Computer . Twente, Netherlands: Univ of Twente Dept of Computer Science, 1996.Science, 1996.

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References # 2:References # 2:

Nilsen, Alleen Pace, and Don L. F. Nilsen. “Computer Humor,” and “Internet Influences.” Encyclopedia of 20th Century American Humor. Westport, CT: Greenwood, 2000, 97-100 and 165-168.

Nilsen, Don L. F., Alleen Pace Nilsen, and Nathan H. Combs. “Teaching a Computer to Speculate.” Computers and the Humanities. 22 (1988): 193-201.

Nilsen, Kelvin, and Alleen Pace Nilsen. “Literary Nilsen, Kelvin, and Alleen Pace Nilsen. “Literary Metaphors and Other Linguistic Innovations in Metaphors and Other Linguistic Innovations in Computer Language” (Clark, 166-176).Computer Language” (Clark, 166-176).

Raskin, Victor. Raskin, Victor. Semantic Mechanisms of HumorSemantic Mechanisms of Humor. Boston, . Boston, MA: Reider/Kluwer, 1985.MA: Reider/Kluwer, 1985.

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References # 3:References # 3:

Raymond, Eric S. Raymond, Eric S. The New Hacker’s Dictionary, 2The New Hacker’s Dictionary, 2ndnd Edition Edition. . Cambridge, MA: MIT Press, 1993.Cambridge, MA: MIT Press, 1993.

Roberts, Steven K. “Artificial Intelligence.” in Roberts, Steven K. “Artificial Intelligence.” in Writing and Writing and Reading Across the Curriculum, 2Reading Across the Curriculum, 2ndnd Edition Edition. Laurence . Laurence Behrens and Leonard J. Rosen. Boston, MA: Litle, Brown, Behrens and Leonard J. Rosen. Boston, MA: Litle, Brown, 1985, 214-222.1985, 214-222.

Rosch, Eleanor. “On the Internal Structure of Perceptual and Rosch, Eleanor. “On the Internal Structure of Perceptual and Semantic Categories.” in Semantic Categories.” in Cognitive Development and the Cognitive Development and the Acquisition of LanguageAcquisition of Language. Ed. T. Moore. New york, NY: . Ed. T. Moore. New york, NY: Academic Press, 1973.Academic Press, 1973.

Schank, Roger C., and Robert Abelson. Schank, Roger C., and Robert Abelson. Scripts, Plans, Goals, Scripts, Plans, Goals, and Understanding: An Inquiry Into Human Knowledge and Understanding: An Inquiry Into Human Knowledge StructuresStructures. Hillsdale, NJ: Lawrence Erlbaum, 1977.. Hillsdale, NJ: Lawrence Erlbaum, 1977.

Siegel, David. Siegel, David. Creating Killer Web SitesCreating Killer Web Sites. Indianapolis, IN: . Indianapolis, IN: Hayden Books, 1996.Hayden Books, 1996.

49 1 computer language by don l. f. nilsen and alleen pace nilsen

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