Introduction
The English-Urdu Gaming Parallel Corpora is a curated bilingual dataset designed to support game localization, machine translation, and language model training for the Gaming industry. It consists of over 50,000 sentence pairs, professionally translated between English and Urdu, capturing the linguistic and cultural depth of gaming content.
Dataset Content
•Volume and Translator Diversity•Total Sentence Pairs: 50,000+
•Contributors: Over 200 native and professional translators
•Source: All content is original and tailored specifically for the Gaming domain
•Sentence Length: 7 to 25 words
•Sentence Types: Includes simple, compound, and complex sentences
•Forms Covered: Interrogative, imperative, affirmative, and negative sentences
•Voice Diversity: Sentences written in both active and passive voice
•Stylistic Coverage: Includes idioms, metaphors, gaming slang, and figurative expressions
•Discourse Elements: Contains conjunctions, logical connectors, and transitional phrases for natural flow
•Bidirectional Structure: Includes English to Urdu and Urdu to English translations for robust model training
Domain-Specific Focus
•Gaming Language Coverage
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Terminology:
Covers in-game elements, UI/UX, controls, multiplayer features, and genre-specific phrases
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Dialogue Content:
Includes NPC dialogue, tutorial lines, mission briefings, walkthroughs, and strategy guidance
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Communication Scenarios:
Reflects live chat, support queries, and multiplayer messaging
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Cross-Domain Inclusion:
Contains relevant terms from adjacent domains like entertainment, esports, virtual worlds, and AR/VR
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File Formats:
Delivered in Excel, with optional conversion to JSON, TMX, XML, XLIFF, XLS, or other standard formats
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Structure Fields:
Serial Number, Unique ID, Source Sentence, Source Word Count, Target Sentence, Target Word Count
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Sentence Alignment:
Sentence-level parallel pairs with consistent formatting for MT pipelines
Usage and Applications
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Machine Translation:
Train and fine-tune domain-specific MT engines for gaming content
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Game Localization:
Adapt games across English-Urdu markets while preserving nuance and playability
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NLP Tools:
Power predictive keyboards, grammar checkers, spelling correction, and sentence completion models
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LLM Fine-Tuning:
Strengthen bilingual comprehension and translation capabilities in large language models
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Dialogue Systems:
Enable context-aware, conversational AI for in-game or support environments
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Bilingual Retrieval:
Use for cross-language search, sentence matching, and similarity scoring
Alignment Confidence and Quality Assurance
•All translations are manually verified by native bilingual experts for accuracy, naturalness, and domain relevance
•Each sentence pair is reviewed to ensure semantic alignment and stylistic consistency
•Quality checks include internal audits, reviewer feedback loops, and alignment validation metrics
Tokenization and Preprocessing
•Dataset is provided in raw, untokenized form by default
•Optional preprocessing available on request, including:
•Format-specific encoding for MT or LLM use
Secure and Ethical Collection
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Data Collection Platform:
Created using FutureBeeAI’s proprietary platform, Yugo
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Data Security:
All data was collected, stored, and processed in a secure environment with no external exposure
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Privacy Assurance:
Contains no personally identifiable information
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IP Safety:
All content is original, created exclusively for this corpus, and free of third-party intellectual property
Updates and Customization
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Continuous Expansion:
Regularly updated with new sentence pairs and linguistic structures
•Named Entity Recognition (NER)
•Translation Quality Ranking
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Custom Dataset Collection:
Available for any language pair or domain on request
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Sentence Classification:
Organize by subdomain, difficulty, sentence type, or discourse function
Licensing
This dataset is developed and maintained by FutureBeeAI. It is available for commercial use under flexible licensing terms for enterprise, research, and application development.
