Machine Translation (MT): A Comprehensive Guide
Machine Translation (MT)
What is Machine Translation?
Machine Translation (MT) refers to computerized systems that produce translations with or without human assistance. These systems differ from computer-based translation tools that support translators by providing access to online dictionaries and terminology databases.
Translation Memory (TM)
Translation Memory is a database that stores previously translated text segments (sentences or paragraphs) as pairs. It works alongside translation software to assist translators.
Benefits of TM:
- Automates translation of repetitive text.
- Ensures consistency in terminology and style.
- Provides suggestions for similar content and specific terms.
Challenges of TM:
- Difficulties with gender and number agreement.
- Handling polysemy (words with multiple meanings).
- Repetitive phrasing and unnatural language flow.
- Incomplete or inaccurate translations due to context limitations.
Types of MT Errors
MT systems often produce errors that differ from those made by human translators, such as incorrect prepositions, articles, pronouns, and verb tenses. Post-editing is typically required to correct these errors.
The Future of MT
Future MT systems aim to improve in the following areas:
- Text analysis and understanding.
- Handling gender and number agreement.
- Pronoun usage and reference resolution.
- Context and subject matter recognition for accurate translation of polysemous terms.
- Style recognition and adaptation.
Basic Functions of MT
- Dissemination: Producing translations of publishable quality with human assistance.
- Assimilation: Providing translations that convey the general meaning, even if the quality is not perfect.
- Interchange: Facilitating communication between individuals who speak different languages, where the focus is on conveying information rather than achieving perfect accuracy.
- Database Access: Assisting users in accessing information from databases in foreign languages.
Using MT for High-Quality Documents
MT can be cost-effective for large-scale translation projects, particularly for technical documentation within specific domains. However, certain conditions must be met:
- The text should be technical in nature, such as manuals or reports, rather than literary or legal documents.
- The domain should be well-defined and consistent.
- Post-editing is essential to ensure quality.
Basic MT Approaches
- Direct Translation: Designed for a specific language pair.
- Interlingua Approach: Converts source language text into an intermediate representation before generating the target language text.
- Transfer Approach: Uses separate abstract representations for both source and target languages, with a transfer stage in between.
History of MT
The concept of using machines for translation dates back to the 17th century. Early proposals and prototypes emerged in the 20th century, but the complexity of language posed significant challenges. The ALPAC report in the 1960s highlighted these challenges and led to a decline in funding for MT research.
Acronyms
- FAHQT: Fully Automatic High Quality Translation
- HAMT: Human-Aided Machine Translation
- MAHT: Machine-Aided Human Translation