1. Designing a Machine Translation Project Lori Levin and Alon Lavie Language Technologies Institute Carnegie Mellon University CATANAL Planning Meeting Barrow, Alaska March 8-9, 2001

2. CATANAL Meeting - Barrow Alaska Outline History of MT--See Wired magazine May 2000 issue. Available on the web. How well does it work? Procedure for designing an MT project. Choose an application: What do you want to do? Identify the properties of your application. Methods: knowledge-based, statistical/corpus based, or hybrid. Methods: interlingua, transfer, direct Typical components of an MT system. Typical resources required for an MT system.

3. March 8-9, 2001CATANAL Meeting - Barrow Alaska How well does it work? Example: SpanAm Handout: Example from the SpanAm system of the Pan American Health Organization. Probably the best Spanish-English MT system. Around 20 years of development.

4. March 8-9, 2001CATANAL Meeting - Barrow Alaska How well does it work? Example: Systran Try it on the Altavista web page. Many language pairs are available. Some language pairs might have taken up to a person-century of development. Can translate text on any topic. Results may be amusing.

5. March 8-9, 2001CATANAL Meeting - Barrow Alaska How well does it work? Example: KANT Translates equipment manuals for Caterpillar. Input is controlled English: many ambiguities are eliminated. The input is checked carefully for compliance with the rules. Around 5 output languages. The output might be post-edited. The result has to be perfect to prevent accidents with the equipment.

6. March 8-9, 2001CATANAL Meeting - Barrow Alaska How well does it work? Example: JANUS Translates spoken conversations about booking hotel rooms or flights. Six languages: English, French, German, Italian, Japanese, Korean (with partners in the C-STAR consortium). Input is spontaneous speech spoken into a microphone. Output is around 60% correct. Task Completion is higher than translation accuracy: users can always get their flights or rooms if they are willing to repeat 40% of their sentences.

7. March 8-9, 2001CATANAL Meeting - Barrow Alaska How well does it work? Speech Recognition Jupiter weather information: 1-888-573-8255. You can say things like “what cities do you know about in Chile?” and “What will be the weather tomorrow in Santiago?”. Communicator flight reservations: 1-877-CMU-PLAN. You can say things like “I’m travelling to Pittsburgh.” Speechworks demo: 1-888-SAY-DEMO. You can say things like “Sell my shares of Microsoft.” These are all in English, and are toll-free only in the US, but they are speaker-independent and should work with reasonable foreign accents.

8. March 8-9, 2001CATANAL Meeting - Barrow Alaska Different kinds of MT Different applications: for example, translation of spoken language or text. Different methods: for example, translation rules that are hand crafted by a linguist or rules that are learned automatically by a machine. The work of building an MT program will be very different depending on the application and the methods.

9. March 8-9, 2001CATANAL Meeting - Barrow Alaska Procedure for planning an MT project Choose an application. Identify the properties of your application. List your resources. Choose one or more methods. Make adjustments if your resources are not adequate for the properties of your application.

10. March 8-9, 2001CATANAL Meeting - Barrow Alaska Choose an application: What do you want to do? Exchange email or chat in Mapudungun and Spanish. Translate Spanish web pages about science into Mapudungun so that kids can read about science in their language. Scan the web: “Is there any information about such-and- such new fertilizer and water pollution?” Then if you find something that looks interesting, take it to a human translator. Answer government surveys about health and agriculture (spoken or written). Ask directions (“where is the library?”) (spoken). Read government publications in Mapudungun.

11. March 8-9, 2001CATANAL Meeting - Barrow Alaska Identify the properties of your application. Do you need reliable, high quality translation? How many languages are involved? Two or more? Type of input. One topic (for example, weather reports) or any topic (for example, calling your friend on the phone to chat). Controlled or free input. How much time and money do you have? Do you anticipate having to add new topics or new languages?

12. March 8-9, 2001CATANAL Meeting - Barrow Alaska Do you need high quality? Assimilation: Translate something into your language so that you can: –understand it--may not require high quality. –evaluate whether it is important or interesting and then send it off for a better translation-- does not require high quality. –use it for educational purposes--probably requires high quality.

13. March 8-9, 2001CATANAL Meeting - Barrow Alaska Do you need high quality? Dissemination: Translate something into someone else’s language e.g., for publication. Usually should be high quality.

14. March 8-9, 2001CATANAL Meeting - Barrow Alaska Do you need high quality? Two-Way: e.g., chat room or spoken conversation May not require high reliability on correctness if you have a native language paraphrase. –Original input : I would like to reserve a double room. –Paraphrase: Could you make a reservation for a double room.

15. March 8-9, 2001CATANAL Meeting - Barrow Alaska Type of Input Formal text: newspaper, government reports, on-line encyclopedia. –Difficulty: long sentences Formal speech: spoken news broadcast. –Difficulty: speech recognition won’t be perfect. Conversational speech: –Difficulty: speech recognition won’t be perfect –Difficulty: disfluencies –Difficulty: non-grammatical speech Informal text: email, chat –Difficulty: non-grammatical speech

16. March 8-9, 2001CATANAL Meeting - Barrow Alaska Resources People who speak the language. Linguists who speak the language. Computational linguists who speak the language. Text on paper. Text on line. Comparable text on paper or on line. Parallel text on paper or on line. Annotated text (part of speech, morphology, etc.) Dictionaries (mono-lingual or bilingual) on paper or online. Recordings of spoken language. Recordings of spoken language that are transcribed. Etc.

17. March 8-9, 2001CATANAL Meeting - Barrow Alaska Methods: Knowledge-Based Knowledge-based MT: a linguist writes rules for translation: –noun adjective --> adjective noun Requires a computational linguist who knows the source and target languages. Usually takes many years to get good coverage. Usually high quality.

18. March 8-9, 2001CATANAL Meeting - Barrow Alaska Methods: statistical/corpus-based Statistical and corpus-based methods involve computer programs that automatically learn to translate. The program must be trained by showing it a lot of data. Requires huge amounts of data. The data may need to be annotated by hand. Does not require a human computational linguist who knows the source and target languages. Could be applied to a new language in a few days. At the current state-of-the-art, the quality is not very good.

19. March 8-9, 2001CATANAL Meeting - Barrow Alaska Methods: Interlingua An interlingua is a machine-readable representation of the meaning of a sentence. –I’d like a double room/Quisiera una habitacion doble. –request-action+reservation+hotel(room-type=double) Good for multi-lingual situations. Very easy to add a new language. Probably better for limited domains -- meaning is very hard to define.

20. March 8-9, 2001CATANAL Meeting - Barrow Alaska Multilingual Interlingual Machine Translation Instructions: Delete sample document icon and replace with working document icons as follows: Create document in Word. Return to PowerPoint. From Insert Menu, select Object… Click “Create from File” Locate File name in “File” box Make sure “Display as Icon” is checked. Click OK Select icon From Slide Show Menu, Select Action Settings. Click “Object Action” and select “Edit” Click OK

21. March 8-9, 2001CATANAL Meeting - Barrow Alaska Methods: Transfer A transfer rule tells you how a structure in one language corresponds to a different structure in another language: –an adjective followed by a noun in English corresponds to a noun followed by an adjective in Spanish. Not good when there are more than two languages -- you have to write different transfer rules for each pair. Better than interlingua for unlimited domain.

22. March 8-9, 2001CATANAL Meeting - Barrow Alaska Methods: Direct Direct translation does not involve analyzing the structure or meaning of a language. For example, look up each word in a bilingual dictionary. Results can be hilarious: “the spirit is willing but the flesh is weak” can become “the wine is good, but the meat is lousy.” Can be developed very quickly. Can be a good back-up when more complicated methods fail to produce output.

23. March 8-9, 2001CATANAL Meeting - Barrow Alaska Components of a Knowledge-Based Interlingua MT System Morphological analyzer: identify prefixes, suffixes, and stem. Parser (sentence-to-syntactic structure for source language, hand-written or automatically learned) Meaning interpreter (syntax-to-semantics, source language). Meaning interpreter (semantics-to-syntax, target language). Generator (syntactic structure-to-sentence) for target language.

24. March 8-9, 2001CATANAL Meeting - Barrow Alaska Resources for a knowledge-based Interlingua MT system Computational linguists who know the source and target languages. As large a corpus as possible so that the linguists can confirm that they are covering the necessary constructions, but the size of the corpus is not crucial to system development. Lexicons for source and target languages, syntax, semantics, and morphology. A list of all the concepts that can be expressed in the system’s domain.

25. March 8-9, 2001CATANAL Meeting - Barrow Alaska Components of Example Based MT: a direct statistical method A morphological analyzer and part of speech tagger would be nice, but not crucial. An alignment algorithm that runs over a parallel corpus and finds corresponding source and target sentences. An algorithm that compares an input sentence to sentences that have been previously translated, or whose translation is known. An algorithm that pulls out the corresponding translation, possibly slightly modifying a previous translation.

26. March 8-9, 2001CATANAL Meeting - Barrow Alaska Resources for Example Based MT Lexicons would improve quality of translation, but are not crucial. A large parallel corpus (hundreds of thousands of words).

27. March 8-9, 2001CATANAL Meeting - Barrow Alaska “Omnivorous” Multi-Engine MT: eats any available resources

28. March 8-9, 2001CATANAL Meeting - Barrow Alaska Approaches we have in mind Direct bilingual-dictionary lookup: because it is easy and is a back-up when other methods fail. Generalized Example-Based MT: because it is easy and fast and can be also be a back-up. Instructable Transfer-based MT: a new, untested idea involving machine learning of rules from a human native speaker. Useful when computational linguists don’t know the language, and people who know the language are not computational linguists. Conventional, hand-written transfer rules: in case the new method doesn’t work.