1. Why Can't Computers Use Language As Well As People Do? Victoria Muehleisen Associate Professor

2. Tasks which computers do better than humans Calculating numbers: Computers are faster and more accurate than people. Searching and retrieving information: Computers don‘t “forget” where information is. Recognizing patterns (such as “enhancing” a photograph): Computers can compare many pieces of information very quickly.

3. However, when it comes to language, computers leave much to be desired.

4. Three programs in this Powerbook Spell Checking (in TextEdit) Speech Recognition (with Apple Speakable Items) Translation (with Sherlock) You’ll see that each program does well with things, but poorly with others.

5. Spell Checking It‘s a kind of pattern matching. It checks the words you type against words in its dictionary.

6. Problems with Spell Checking It works fine for words in the dictionary, but a lot of words aren‘t in the dictionary! It usually doesn‘t catch a mistake when the mistake is an actual word (just the wrong word).  Demonstration

7. Speech Recognition A computer first must recognize the individual sounds, then the words, then the meanings.

8. Problems with Speech Recognition The program can only recognize a certain set of words, but in natural languages, there are many different ways to express the same message.  Demonstration

9. More problems with Speech Recognition Different speakers have different voices and different accents. Even one person sounds different at different times (for example, talking quickly, talking while sick with a cold.)

10. Translation This is one of the most complicated things we ask computers to do with language. To translate, a person or a computer must understand individual words, understand the sentences, and understand the intended meaning in one language.

11. Translation Then the translator must find equivalent words and sentences in the other language.  Demonstration

12. Problems with Translation There are many things which make translation difficult, both for people and for computers. We’ll see several more examples in the rest of this lecture.

13. Why can’t computers do better? Of course, computers don‘t do anything with language by themselves. They are programmed by people!

14. So the question really is… Why can‘t people program computers to deal with language as well as people can?

15. In order to program computers to use language … 1. We have to understand the “rules” of language. 2. We have to express those rules in a way that computers can use.

16. People working on this problem Linguists: people who study the rules and patterns of language Computer scientists and applied linguists: people creating programs based on the rules and patterns

17. Understanding the Rules: One Simple Rule of English To form the past tense of most verbs, add -ed to the present tense form. live → lived need → needed

18. We need to list the conditions and exceptions. Some verbs are irregular (wrote, saw), and these must be listed individually in the program. Speech production and speech recognition programs would have to know that -ed has different pronunciations: /d/ in lived, /id/ in needed, and /t/ in slipped.

19. Computers can easily “learn” this kind of simple rule, but... …even with a rule so simple there may be variations that are hard to include in the program.  She dived into the lake. (Used in many English speaking countries)  She dove into the lake. (Used in some parts of North America)

20. Many rules are more complex. English speakers learn the difference between “the” and “a” at an early age, but we never learn explicit rules. Linguists have tried to describe the rules for using “the” and “a”, but there is still no complete description.

21. A similar example in Japanese You learned how to use “wa” and “ga” at an early age, but there is still no complete set of rules which can be used by adults learning Japanese.

22. Many patterns in language are still not completely understood… …and if we don’t understand the patterns, we can’t write computer programs.

23. An example: Input: お湯がありますか？お茶を飲みたいです。 Sherlock’s translation: Is there a hot water? We would like to drink the tea, is. My translation: Is there any hot water? I want some tea.

24. Another example of rules When translating from Japanese to English or English to Japanese, we need rules to describe the differences in basic word order: Japanese: Subject - Object-Verb  私は、本を買った。 English: Subject - Verb - Object  I bought a book.

25. Word order rules in a computer program The difference in word order is something we can easily make a rule for and put into a computer program, as long as the sentence is simple.

26. Sherlock’s translation Input: Cats like mice. Output: 猫がマウスを好む。

27. But not all sentences are this easy… Consider a sentence with more than one clause: Input: I love skiing, so whenever I get a chance, I do it. Sherlock: 私はするそれをスキー、従って私 がチャンスを得る時はいつでも、私愛する。

28. A human translation (my husband’s) 私は、スキが好きです。チャンスがあれば、 いつでもスキをやります。

29. There are many more difficulties for Sherlock For example, English sentences must always have a subject, but in Japanese, the subject is often not mentioned.

30. What is the subject of this sentence? 雨がすきで、雨が降ると雨をみる。 If I tell you that it is from a autobiographical ( 自叙） essay, you can easily guess.

31. Human translation(mine): Input: 雨がすきで、雨が降ると雨をみる。 Output: I like rain, so when it rains, I watch it. I know from the context that the person who likes rain and the person who watches the rain are both “I”.

32. Sherlock’s translation Input: 雨がすきで、雨が降ると雨をみる。 Output: Liking the rain, when the rain falls, you see the rain.

33. My translation and Sherlock’s translation are different because I understand the context of the sentence.

34. Another example of the importance of context (Students of Japanese learn this one in class!) In a restaurant: 「私は、うなぎです。」

35. My translation: “I’ll have eel.” Sherlock’s: “I am the eel.”

36. Possibility for improvement It is possible to put more information about grammar structure and contexts into computer programs.

37. A better spell checker TextEdit is free software, but a more expensive program might catch mistakes like this one: “Can you sea this mistake?” “See” is a verb, but “sea” is a noun.

38. A better translation program Sherlock is a free program, but a more expensive would probably know that we don’t say “a hot water.” お湯がありますか？⇒ Is there any hot water?

39. A better translation program It might even be possible to make a program that would know that in an autobiographical essay, the subject is often “I”. 雨がすきで、雨が降ると雨をみる。 I like rain, so when it rains, I watch it.

40. But there’s a more serious difficulty… In the widest sense, context includes the whole world, including knowledge of social relationships. Humans can easily use this knowledge, but can computers?

41. An example of social context 優美子：宝くじ一等当たったのよ。 貴子：うそ！

42. Sherlock’s translation Yumiko: Lottery first class it hit, is. Takako: Lie!

43. 「うそ！」 ≠ “lie!” We know that if Yumiko and Takako are friends, Takako is not calling her friend a liar. We can tell this both by the context and by the pronunciation: 「うっそ〜」.

44. A better translation Yumiko: I won first prize in the lottery. Takako: No! I don’t believe it!

45. “No! I don’t believe it!” In this case too, the real meaning is not the same as the literal meaning. Takako does believe what Yumiko said, but she is very surprised. This expression shows her feelings.

46. Real meaning vs. literal meaning It’s easy for humans to learn that the real meaning is not always the literal meaning. Although I never learned this use of うそ in Japanese class in the U.S., I quickly learned it when I got to Japan. However, it’s hard to imagine how a computer program could “learn” this kind of thing.

47. Summary If linguists can write a language rule that does not depend on the context, it’s easy for computer scientists to write a computer program using the rule.

48. But if the rule is not understood well, or if the rule depends on the context, it’s very difficult, or maybe impossible, to write a program using it.

49. In the future, we can expect that computers will get better and better at translating “straight forward” texts (e.g., texts that just give information). However, there are some things that computers might never be able to do.

50. If you want to learn more… Go to the web sites on the handout  Japanese web sites about linguistics  The Linguistic Society of America (check out the videos!)  The Linguist Network

51. Classes at the International College of Waseda  CO 201 Introduction to Language Studies  CO 202 Introduction to Communication  CO 203 Introduction to Application of Language Studies  GE 111 Introduction to Computer Literacy （情 報処理入門）

52. You can find the web links and this PowerPoint lecture on my web page:

53. Any questions?