A CrossLingual Grammar Model and its Application to JapaneseSpanish Machine Translation

1
A Cross-Lingual Grammar Model and its Application
to Japanese-Spanish Machine Translation

• Manuel Medina González and Hirosato Nomura
• Kyushu Institute of Technology

2
Outline

• Introduction
• Spanish Features and Considerations when
  translating.
• Parts of speech
• Voices
• System
• Summary
• Conclusions

3
Introduction

• Current Machine Translation Systems output
  incorrect sentences when translating from
  Japanese to Spanish.

http//www.worldlingo.com/en/products_services/wor
ldlingo_translator.html
4
Introduction

• The reason is because English is used as
  intermediate language, thus, leading to loss of
  grammatical information due to the differences
  between the languages.

http//www.worldlingo.com/en/products_services/wor
ldlingo_translator.html
5
Introduction

• The idea is simple To translate directly from
  Japanese to Spanish.

El niño juega en el parque
????????

• In order to accomplish this, the way the analysis
  is performed must be adapted to support Spanish
  features

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Introduction

• We base our model on ALT J/E Machine Translation
  System Model, with some modifications.

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Model
Source Language
Target Language
Direct Method
Corpus-based Translation

• Noun features
• Determiner
• Subjunctive Mood

Analysis
Generation
Transfer Method
Conversion
Intermediate Language(PIVOT)
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Model
Determining the missing information by predicting
the result as we analyze the sentence.
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Outline

• Introduction
• Spanish Features and Considerations when
  translating.
• Parts of speech
• Voices
• System
• Summary
• Conclusions

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Spanish Features Nouns

• Gender
• Table Feminine.
• Book Masculine.
• Number
• Table Singular
• Tables Plural
• Nouns features decide
• almost all the possible
• changes a Spanish
• sentence can suffer.

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Spanish Features Nouns

• ????????????????????

??
?? ? ??? ?? ? ??? Zero??? ? ???
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Semantic Categorization

• ALT J/E Semantic Categorization (2710 different,
  non-exclusive categories).

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Spanish Features Adjectives

• As in English, only one category exists.
• 2 verbs mainly used Ser and Estar. Both are
  equivalent to English To be verb.
• The meaning is different depending on the verb
  used.

Yo soy feliz
?????
Yo estoy feliz
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Spanish Features Adjectives

• Creation of categories
• Temporary state Sad
• Permanent feature Boring, interesting
• Weather
• Weather category is necessary because other 2
  verbs are used Tener and Hacer.

Tengo calor
What you feel
??
The weather
Hace calor
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Spanish Features Adverbs

• Thinking of them as they are in Spanish, we
  create categories as in this language
• Place
• Time
• Mode
• Quantity
• Order
• Affirmation
• Denial
• Doubt
• Addition
• Exclusion

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Spanish Features Verbs

• Tenses
• Japanese 3 (Present, past, future)
• Spanish 16
• Conjugations
• Different conjugation for each person in each
  tense.
• A conjugator system can be made for regular
  verbs, but there are too many rules to consider.

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(No Transcript)
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Reflexive Verbs

• A verb is reflexive if the action returns to its
  performer.
• There are verbs in Japanese that can be reflexive
  and non-reflexive at the same time.

Non-Reflexive
??
Reflexive
??????
??????
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Reflexive Verbs

• Creation of Has-a relationships to determine
  whether if a verb must be treated as reflexive.

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Translation Rules

• Based on ALT J/E Translation Rules.
• Verb
• Particles used in special cases
• Categories of the expected nouns accompaining the
  particles
• Translation of the verb in each case.
• Indication if the verb must be treated as
  reflexive.

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????

• ??? Montar en
• ??? Subir(R) a
• ...

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Outline

• Introduction
• Spanish Features and Considerations when
  translating.
• Parts of speech
• Voices
• System
• Summary
• Conclusions

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Voices

• Passive ??????
• Normal passive
• Indirect object reference
• Passive Reflexive
• Causative ??????
• Coercive
• Permissive

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Voices Model

• Japanese Sentence

Passive, Causative
Identify Voice
Voice, Structure
Predict Result
Pronouns Mood...
Add or change elements
Analyze elements
Not explained deeply here due to the time
limitation

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Outline

• Introduction
• Spanish Features and Considerations when
  translating.
• Parts of speech
• Voices
• System
• Summary
• Conclusions

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System

• Named JEMS Japanese Español Machine
  translation System.

Translated Sentence

JEMS Core
Semantic Categories
Translation Rules
Dictionary
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JEMS
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Tests and Results

• JEMS compared against Worldlingo.
• Sentences taken from books like Momotaro,
  Megane usagi, 3 nen netaro etc.
• Human-Translating the sentences, then inputting
  them into the systems and checking the output.

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Tests and Results
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Tests and Results
Possible Expected Outputs
Input

• ???????????

Finalmente la primavera llegó. Finalmente la
primavera ha llegado.
Obtained Output
Resorte usted cada vez más
? ? Spring Spring 1. Primavera 2.
ResorteAnalysis is not complete

• Errors
• Lack of verb
• Incorrect subject
• Incorrect structure

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Outline

• Introduction
• Spanish Features and Considerations when
  translating.
• Parts of speech
• Voices
• System
• Summary
• Conclusions

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Summary

• Indirect Translation from Japanese to Spanish is
  not enough.
• Model based on thinking of the translated
  sentence since the analysis starts.
• Presented just a small part of the analysis
  necessary to translate into Spanish
• Developed a prototype system JEMS to test the
  model. Compared against an existent translation
  system.

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Outline

• Introduction
• Spanish Features and Considerations when
  translating.
• Parts of speech
• Voices
• System
• Summary
• Conclusions

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Conclusions

• Japanese-Spanish Machine Translation is just
  beginning. There are still many issues to be
  solved.
• Need to make the model bigger in order to analyze
  longer sentences.
• Once this model is finished, it can become the
  basis for other research about Machine
  Translation between Japanese and Romance
  Languages.

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Conclusions
Spanish
Me llamo Taro
Italian
Me chiamo Taro
Portuguese

• ??????

Me chamo Taro
French
Je m'appelle Taro