Using morphology to improve Example-Based Machine Translation
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Violetta Cavalli-Sforza
Abstract
We describe how morphological information was used in an Example-Based Arabic-to-English Machine Translation system to produce significant improvement in translation quality on both small and large corpora. We experimented with different methods of generalizing morphology to obtain more candidate source-side matches, while retaining information about the specific input to be translated. This information was then used with adaptation rules and a language model to generate context-appropriate target-side fragments, select and combine them. We outline essential differences between Statistical MT (SMT) and Example-based MT (EBMT), compare ourselves to other EBMT systems used with morphologically complex languages, and justify our choice of EBMT over SMT.
Abstract
We describe how morphological information was used in an Example-Based Arabic-to-English Machine Translation system to produce significant improvement in translation quality on both small and large corpora. We experimented with different methods of generalizing morphology to obtain more candidate source-side matches, while retaining information about the specific input to be translated. This information was then used with adaptation rules and a language model to generate context-appropriate target-side fragments, select and combine them. We outline essential differences between Statistical MT (SMT) and Example-based MT (EBMT), compare ourselves to other EBMT systems used with morphologically complex languages, and justify our choice of EBMT over SMT.
Chapters in this book
- Prelim pages i
- Table of contents v
- Preface vii
- Introduction 1
- Linguistic resources for Arabic machine translation 15
- Using morphology to improve Example-Based Machine Translation 23
- Using semantic equivalents for Arabic-to-English 49
- Arabic preprocessing for Statistical Machine Translation 73
- Preprocessing for English-to-Arabic Statistical Machine Translation 95
- Lexical syntax for Arabic SMT 109
- Automatic rule induction in Arabic to English machine translation framework 135
- Index 155
Chapters in this book
- Prelim pages i
- Table of contents v
- Preface vii
- Introduction 1
- Linguistic resources for Arabic machine translation 15
- Using morphology to improve Example-Based Machine Translation 23
- Using semantic equivalents for Arabic-to-English 49
- Arabic preprocessing for Statistical Machine Translation 73
- Preprocessing for English-to-Arabic Statistical Machine Translation 95
- Lexical syntax for Arabic SMT 109
- Automatic rule induction in Arabic to English machine translation framework 135
- Index 155
