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Created By: Benjamin J. Van Someren.  Natural Language Translation – Translating one natural language such as German to another natural language such.

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Presentation on theme: "Created By: Benjamin J. Van Someren.  Natural Language Translation – Translating one natural language such as German to another natural language such."— Presentation transcript:

1 Created By: Benjamin J. Van Someren

2  Natural Language Translation – Translating one natural language such as German to another natural language such as English in a machine. Referred to as Machine Translation  Natural Language Processing – Allowing a machine to understand the meaning of natural languages such as German, French, and English.  Both greatly involve Artificial Intelligence Statistics Linguistics

3  Linguistics - The scientific study of language and its structure, including the study of morphology, phonetics, syntax, and semantics.  Morphology - The study and description of word formation (involving inflection, derivation, and compounding) in language.  Phonetics - The speech sounds of a language or group of languages.

4  Syntax - In linguistics, the study of the rules that govern the ways in which words combine to form phrases, clauses, and sentences.  Semantics – In linguistics, the study of meaning in a language.

5 From Language A ----------------------- Sentence(s) Phrase(s) etc Translate To Language B -------------------- Sentence(s) Phrase(s) etc Give To Receive from

6  Direct Translation Dictionary Lookup  Example Good, right?

7  Example Peter hat das Buch von Maria gelesen  Peter has the book of Mary read  Allowing for grammar So how is it done?

8  Create a word to word matrix. E1E2E3E4E5E6E7 PeterXG1 HatXG2 DasXG3 BuchXG4 VanXG5 MariaXG6 gelesenXG7 PeterhasthebookofMaryread

9  Apply IBM Model 1 Statistical Formula  And you get 

10  Words are assigned their best translation word, despite its position within the phrase or sentence.  Can only allow 1-to-n word alignment not n-to-1 or n-to-m

11  So where are we at? Machine Translation Triangle

12  Ambiguous  Highly contextual  Implicit  Often imprecise

13  Lexical Ambiguity - When a word can be understood in two or more possible senses or ways. Any word that has multiple meanings  Structural ambiguity – When a sentence or clause is unclear about what is meant. "Mary had a little lamb." With mint sauce?

14  Denotation - The central meaning of a word. The denotation of "silly" today is not what it was in the 16th century. Today it means “weak in intellect” or “foolish” In the 16th century it meant "happy" or "innocent.“  Connotation - The personal or emotional associations aroused by words. A possible example of such a change is the word vicious. Originally derived from vice, it meant "extremely wicked." However, in the modern British usage it is commonly used to mean "fierce," as in “the brown rat is a vicious animal”.

15  Implication - When the speech is intended to mean something but does not communicate it directly. “deer!" → implicit meaning: "We must STOP the car now!”  Allegory: The expression by means of symbolic fictional figures and actions of truths or generalizations about human existence. The book "Moby Dick" by Herman Melville is a clear example of allegory; where the great white whale is more than a very large, aquatic mammal; it becomes a symbol for eternity, evil, dread, mortality, and even death, something so great and powerful that we humans cannot even agree on what it might mean.

16  Metaphor - This refers to the non-literal meaning of a word. "out of the blue“  Homonym: When different words are pronounced, and possibly spelled, the same way. examples:  to, too, two;  bat the animal, bat the stick, and bat as in “bat the eyelashes”

17  Interlingua - is a system for representing the meanings and communicative intentions of language. Made up of 3 parts (S, N, L)  S - a collection of representation symbols, where each symbol denotes a particular aspect of meaning or intention.  N - a notation, within which symbols can be composed into meanings.  L - a lexicon, namely a collection of words of a human language such as English, in which each lexical element is associated directly or indirectly with one or more symbols from S. Interlingual systems typically include one lexicon for each language.

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19 The more languages the better

20  Style and emphasis of the original text are lost and so actual text behaves more like paraphrased text.  There is no clear way in which to create this language-neutral meaning representation.

21  Semantic network (SN) A model of a conceptual structure consisting of a set of concepts and the cognitive relations between them. It is represented by a graph where the concepts correspond to the nodes and the relations correspond to the arcs.

22  Stands for “Multilayered Extended Semantic Network”  Is both a knowledge representation paradigm and a language for meaning representation of natural language expressions.  It specifies conceptual structures by using 140 predefined relations/function.

23 Not every concept can be reduced to a semantically primitive elements. Natural Language consists of both language and metalanguage.

24  1. A word or a word group designating the concept and representing it externally.  2. A collection of relations to other concepts.  3. A complex pattern of perceptual (mostly visual) origin.  Not all three features must be present with every concept.

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27  MultiNet embeds all of its entities into a multidimensional space.

28  Determiners - modifiers which, together with nouns, result in expressions whose reference is determined with regard to the referent or noun. “this house”, “a house”, “every house”  Quantificators - modifiers which, together with nouns, result in expressions whose reference is described by the amount of a substance. “almost all houses”, “some milk”, “many houses”,

29 “Max gave his brother several apples.” “This was a generous gift.” “Four of them were rotten.”

30 When we have a working interlingua it can be used for multiple applications.

31 Any questions?

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